CN111369431A - Image processing method and device, readable medium and electronic equipment - Google Patents
Image processing method and device, readable medium and electronic equipment Download PDFInfo
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Abstract
The disclosure relates to an image processing method, an image processing device, a readable medium and an electronic device, and relates to the technical field of image processing, wherein the method comprises the following steps: according to a preset color recognition algorithm, obtaining a plurality of theme colors of an image to be processed, taking the theme color meeting a preset condition in the theme colors as a basic color, determining a harmonious color of the basic color and an inharmonious color of the basic color, taking the theme color belonging to the inharmonious color in the theme colors as a color to be replaced, and replacing the color to be replaced in the image to be processed according to the harmonious color to obtain a target image. According to the method and the device, the theme color in the image to be processed is firstly identified, and then the color which is not harmonious with the basic color in the theme color is replaced to obtain the target image with harmonious color, so that the effect of beautifying the image is achieved, the implementation is simple, the calculation amount is small, and the image processing efficiency is improved.
Description
Technical Field
The present disclosure relates to the field of image processing technologies, and in particular, to a method and an apparatus for processing an image, a readable medium, and an electronic device.
Background
With the continuous development of terminal technology and image processing technology, the image processing operation provided by the intelligent terminal is more and more abundant. For example, the smart terminal may beautify the image according to the colors contained in the image. Under a common condition, a large number of images in reality need to be collected in advance, technicians manually beautify the images, and a machine learning algorithm is used for learning the process of beautifying the images, so that a large amount of manpower and time are consumed, the machine learning algorithm is complex to implement, the calculation amount is large, and the image processing efficiency is low.
Disclosure of Invention
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
In a first aspect, the present disclosure provides a method for processing an image, the method comprising:
acquiring a plurality of theme colors of an image to be processed according to a preset color recognition algorithm;
taking the theme colors meeting preset conditions in the plurality of theme colors as basic colors, and determining harmonious colors of the basic colors and discordant colors of the basic colors;
taking the subject color belonging to the anharmonic color among the plurality of subject colors as a color to be replaced;
and replacing the color to be replaced in the image to be processed according to the harmonious color to obtain a target image.
In a second aspect, the present disclosure provides an apparatus for processing an image, the apparatus comprising:
the acquisition module is used for acquiring a plurality of theme colors of the image to be processed according to a preset color recognition algorithm;
the first determining module is used for taking the theme colors meeting preset conditions in the theme colors as basic colors, and determining harmonious colors of the basic colors and discordant colors of the basic colors;
a second determination module, configured to use the theme color belonging to the anharmonic color in the plurality of theme colors as a color to be replaced;
and the replacing module is used for replacing the color to be replaced in the image to be processed according to the harmonious color so as to obtain a target image.
In a third aspect, the present disclosure provides a computer readable medium having stored thereon a computer program which, when executed by a processing apparatus, performs the steps of the method of the first aspect of the present disclosure.
In a fourth aspect, the present disclosure provides an electronic device comprising:
a storage device having a computer program stored thereon;
processing means for executing the computer program in the storage means to implement the steps of the method of the first aspect of the present disclosure.
According to the technical scheme, the method comprises the steps of firstly identifying an image to be processed according to a preset color identification algorithm to obtain a plurality of theme colors, then taking the theme colors meeting preset conditions in the theme colors as basic colors, determining harmonious colors and inharmonious colors of the basic colors, further taking the theme colors belonging to the inharmonious colors in the theme colors as colors to be replaced, and finally replacing the colors to be replaced according to the harmonious colors to obtain a target image. According to the method, the theme color in the image to be processed is firstly identified, and then the color which is not harmonious with the basic color in the theme color is replaced to obtain the target image with harmonious color, so that the effect of beautifying the image is achieved, a large amount of training data does not need to be collected in advance, the image does not need to be beautified manually, the method is simple to realize, the calculated amount is small, and the efficiency of image processing is improved.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and features are not necessarily drawn to scale.
In the drawings:
FIG. 1 is a flow diagram illustrating a method of processing an image according to an exemplary embodiment;
FIG. 2 is a flow diagram illustrating another method of processing an image according to an exemplary embodiment;
FIG. 3 is a flow diagram illustrating another method of processing an image according to an exemplary embodiment;
FIG. 4 is a flow diagram illustrating another method of processing an image in accordance with an exemplary embodiment;
FIG. 5 is a block diagram illustrating an apparatus for processing an image according to an exemplary embodiment;
FIG. 6 is a block diagram illustrating another image processing apparatus according to an example embodiment
FIG. 7 is a block diagram illustrating another image processing apparatus according to an exemplary embodiment;
FIG. 8 is a block diagram illustrating another image processing apparatus according to an exemplary embodiment;
FIG. 9 is a block diagram of an apparatus shown in accordance with an example embodiment.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order, and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
The term "include" and variations thereof as used herein are open-ended, i.e., "including but not limited to". The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
Fig. 1 is a flowchart illustrating a method of processing an image according to an exemplary embodiment, the method further including, as shown in fig. 1:
For example, the image to be processed may be an image captured by the terminal device by the user (for example, a photo taken by the terminal device), or may be an image selected by the user on the terminal device (for example, an image selected on a display interface of the terminal device). Firstly, the image to be processed may be identified according to a preset color identification algorithm to obtain a plurality of theme colors, and the theme colors may be understood as main colors in the image to be processed, that is, colors with a higher ratio in the image to be processed. The preset color recognition algorithm may be, for example, inputting the image to be processed into a pre-trained color recognition model, where the color recognition model outputs a matching degree of the image to be processed and each color in the color set, and then takes a preset number of colors (e.g., 3) with the highest matching degree as the theme color. The preset color identification algorithm may also be to determine the number of pixel points of each color in the color set in the image to be processed according to the color coordinates of each pixel point in the image to be processed, and use the preset number of colors with the highest number of pixel points as the theme color. The preset color recognition algorithm can also be used for determining the semantic color of each pixel point according to the color coordinate of each pixel point in the image to be processed and combining the mapping relation between the predetermined color coordinate and the semantic color, then determining the number of the pixel points belonging to different semantic colors in the image to be processed, and finally taking the semantic colors with the highest number of the pixel points in the preset number as the theme colors.
And 102, taking the theme color meeting the preset condition in the plurality of theme colors as a basic color, and determining the harmonious color of the basic color and the discordant color of the basic color.
For example, a plurality of theme colors may be screened according to a preset condition, and the theme color meeting the preset condition is used as the basic color. The preset condition may be, for example, a theme color representing a designated object in the image to be processed, and the designated object may be a default object or may be designated by the user according to specific requirements, for example, the designated object may be a person, an animal, or other objects. The preset condition may also be a theme color with the most obvious contrast or a theme color with the largest occupied area in the image to be processed. The preset condition may also be a subject color of a salient region in the image to be processed. After the basic color is determined, the harmonious color and the discordant color corresponding to the basic color can also be determined. For example, a color relationship table may be pre-established according to a color harmony theory, the color relationship table has a plurality of records, each record includes a color, and a harmony color and an inharmony color corresponding to the color, and the harmony color and the inharmony color corresponding to the basic color may be determined by looking up the table. And a color harmony model can be trained in advance, one color is used as the input of the color harmony model, and the color harmony model outputs the harmony color and the inharmonious color corresponding to the color. The basic color may be one color or a plurality of colors, and correspondingly, the harmonious color or the discordant color of each basic color may be one color or a plurality of colors.
And 103, taking the subject color belonging to the inharmonious color in the plurality of subject colors as the color to be replaced.
And 104, replacing the color to be replaced in the image to be processed according to the harmonious color to obtain the target image.
In an example, whether each theme color belongs to an inharmonious color or not is sequentially judged, if the theme color belongs to the inharmonious color, the theme color is expressed to be inharmonious with the basic color, and processing is not needed, and if the theme color belongs to the inharmonious color, the theme color is expressed to be inharmonious with the basic color, and processing is needed, and the theme color is taken as a color to be replaced. And then, replacing the colors to be replaced in the image to be processed according to the harmonious colors to obtain the beautified target image. After the target image is obtained, the target image may be output, for example, displayed on a display interface of the terminal device, stored, or shared through a network. The color to be replaced in the image to be processed is replaced according to the harmonious color, the color to be replaced can be directly replaced by the harmonious color, the harmonious color can also be processed according to the brightness and the saturation of the color to be replaced, the obtained brightness and the saturation are the same as the color to be replaced, only the new color of the chroma is changed, and the color to be replaced is replaced by the new color. Therefore, the theme colors in the target image are all harmonious with the basic colors, so that the target image is more suitable for the impression of human eyes, and the effect of beautifying the image is achieved.
In summary, according to the present disclosure, an image to be processed is first identified according to a preset color identification algorithm to obtain a plurality of theme colors, then a theme color meeting a preset condition in the plurality of theme colors is used as a base color, a harmonious color and an inharmonious color of the base color are determined, a theme color belonging to the inharmonious color in the plurality of theme colors is further used as a color to be replaced, and finally, the color to be replaced is replaced according to the harmonious color to obtain a target image. According to the method, the theme color in the image to be processed is firstly identified, and then the color which is not harmonious with the basic color in the theme color is replaced to obtain the target image with harmonious color, so that the effect of beautifying the image is achieved, a large amount of training data does not need to be collected in advance, the image does not need to be beautified manually, the method is simple to realize, the calculated amount is small, and the efficiency of image processing is improved.
Fig. 2 is a flowchart illustrating another image processing method according to an exemplary embodiment, and as shown in fig. 2, the implementation of step 102 may include:
Specifically, when the basic color is selected, a priority rule may be agreed in advance, then the priority is determined according to the attribute of each theme color, and one or more theme colors with the highest priority are selected as the basic color. The attribute can be understood as a feature of the region where the subject color is located, for example, an object (for example, a person, a sky, an ocean, a river, a lake, a mountain, an animal, a plant, a car, etc.) represented by the region where the subject color is located. It may be the contrast of the region where the subject color is located with the surrounding region, or the region area. It may also be whether the area where the subject color is located is a salient area (which may be understood as a key area detected based on the human visual attention mechanism). For example, the first theme color is any theme color, and if the area where the first theme color is located in the image to be processed is the designated object, the priority of the first theme color is determined to be the first priority. The designated object may be a default object, or may be designated by the user according to specific needs, for example, an object such as a person or an animal. And if the area where the first theme color is located in the image to be processed is the salient area, determining the priority of the first theme color as a second priority, wherein the second priority is smaller than the first priority. Further, if the contrast of the region where the first theme color in the processed image is located is greater than the contrast threshold, or the area of the region is greater than the area threshold (or the area ratio of the region area to the image to be processed is greater than the proportion threshold), it is determined that the priority of the first theme color is a third priority, and the third priority is less than the second priority.
And 1023, determining a harmonious color and an inharmonious color according to a color relation table, wherein the color relation table comprises the harmonious color and the inharmonious color corresponding to each color in the plurality of colors.
Further, a color relation table can be pre-established according to the color harmony theory, wherein the color relation table has a plurality of records, and each record contains a color and a harmonious color and an inharmonious color corresponding to the color. The harmonious color and the discordant color corresponding to the basic color can be determined in a table look-up mode. Different colors are harmonious, and the selection criteria of harmonious colors are different, for example, harmonious colors can be complementary colors, contrasting colors, adjacent colors or four roles of basic colors, and the like, which is not specifically limited by the disclosure. The color relation table can be directly stored in the terminal device or stored in the server, and when the terminal device needs to be used, the color relation table is obtained from the server.
FIG. 3 is a flow chart illustrating another method of processing an image according to an exemplary embodiment, as shown in FIG. 3, step 104 may include:
And 1042, replacing the coordinate value representing the chromaticity in the second color coordinate with the coordinate value representing the chromaticity in the first color coordinate to obtain a third color coordinate.
And step 1043, replacing the color to be replaced in the image to be processed with the color indicated by the third color coordinate to obtain the target image.
For example, first color coordinates of a harmonic color in a preset color space and second color coordinates of a color to be replaced in the preset color space are obtained. And then, replacing the coordinate value representing the chromaticity in the second color coordinate by the coordinate value representing the chromaticity in the first color coordinate to obtain a third color coordinate, wherein the third color coordinate can be understood as that the brightness and the saturation of the color to be replaced are reserved, and the chromaticity is the same as the chromaticity of the harmonious color. And then replacing the color to be replaced with the color indicated by the third color coordinate to obtain the target image, so that the subject color in the target image can be continuously read and unified with the subject color in the image to be processed in the dimension of brightness and saturation, and the beautifying effect is more natural.
Specifically, the preset color space may be, for example: an RGB (english: Red Green Blue, chinese: Red-Green-Blue) color space, an LUV color space, an LAB color space, and the like. If the preset color space is a LUV color space, the first color coordinate is (L1, U1, V1), the second color coordinate is (L2, U2, V2), then U1 and V1 are used to replace U2 and V2, and L2 is retained, then the third color coordinate is (L2, U1, V1). If the preset color space is an LAB color space, the first color coordinate is (L1, a1, B1), the second color coordinate is (L2, a2, B2), then a1 and B1 are used to replace a2 and B2, and L2 is reserved, then the third color coordinate is (L2, a1, B1). If the preset color space is an RGB color space, the first color coordinate is (R1, G1, B1), and the second color coordinate is (R2, G2, B2), the first color coordinate and the second color coordinate may be mapped to the LUV color space, respectively, to obtain (L1, U1, V1) that the first color coordinate corresponds to the LUV color space, and (L2, U2, V2) that the second color coordinate corresponds to the LUV color space, then, U2 and V2 are replaced with U1 and V1, L2 is retained, to obtain (L2, U1, V1), and then (L2, U1, V1) is mapped to the RGB color space to obtain the third color coordinate (R3, G3, B3).
It should be noted that, when determining the color to be replaced in step 103, if the base color is a color, the color to be replaced may be a theme color that is an inharmonious color belonging to the base color among all theme colors. If the basic color is a plurality of colors, all the theme colors may be divided into theme colors adjacent to each basic color, and then the color to be replaced corresponding to one basic color may be a theme color belonging to an inharmonious color of the basic color among the theme colors adjacent to the basic color. Correspondingly, when step 104 is executed, the color to be replaced corresponding to the basic color is also replaced according to the harmonious color of the basic color.
Further, when the color to be replaced is determined in step 103, according to a preset avoidance rule, even if some specified subject colors belong to the inharmonious color, the specified subject colors are not used as the color to be replaced, so as to avoid replacing some colors that the user wants to keep in the image to be processed. The avoidance rule may be, for example, a theme color of the specified avoidance object in the area, and the specified avoidance object may be an object that needs to be avoided and is specified by the user according to specific requirements, for example, the specified avoidance object may be a sky, a plant, or the like. The avoidance rule may also be a theme color within a region marked by the user on the image to be processed.
Fig. 4 is a flowchart illustrating another image processing method according to an exemplary embodiment, and as shown in fig. 4, the implementation of step 101 may include:
And 1013, determining a plurality of theme colors of the image to be processed according to the semantic color of each pixel point.
For example, the color coordinates of each pixel point in the image to be processed may be determined according to a preset color space. And then searching the semantic color corresponding to the color coordinate of each pixel point according to the mapping relation between the preset color space and the semantic color, and taking the semantic color corresponding to the color coordinate of each pixel point as the semantic color of the pixel point. The mapping relationship may be stored in the terminal device in advance, or may be stored in the server, and when the terminal device needs to use the mapping relationship, the mapping relationship is obtained from the server. The mapping relationship can be understood as a correspondence relationship between each color coordinate and a plurality of semantic colors in a preset color space established in advance, that is, each color coordinate corresponds to one semantic color. For example, the mapping relationship may be in the form of a table, where each row in the table contains a color coordinate and a semantic color corresponding to the color coordinate. Color coordinates are a set of numerical values with no explicit meaning. Semantic colors may be understood as real colors in the real world, i.e. colors containing explicit semantics, which may include, for example: red, orange, yellow, green, blue, violet, black, white, gray, and the like.
After the semantic color of each pixel point is determined, the theme color of the image to be processed can be determined according to the distribution number of the semantic colors contained in the image to be processed. The number of pixel points with various semantic colors in the image to be processed can be determined first, then the number of pixel points with different semantic colors is sequenced, a preset number (for example, 3) of semantic colors with the largest number of pixel points is selected as a subject color, the semantic colors with the number of pixel points larger than a preset threshold value can be used as the subject color, the ratio of the number of pixel points with different semantic colors to the total number of pixel points of the image to be processed can be determined, and the semantic colors with the ratio larger than the preset threshold value are used as the subject color. For example, the image to be processed includes 1000 pixel points, and the number of the pixel points with multiple semantic colors is arranged in a descending order, where the semantic color of 420 pixel points is white, the semantic color of 310 pixel points is blue, the semantic color of 205 pixel points is green, and the remaining 65 pixel points are other colors, so that white, blue, and green can be used as the theme color.
Wherein the mapping relationship is obtained by the following steps:
step A, a sample image set is obtained, wherein the sample image set comprises a plurality of sample images.
And step B, determining the number of each color coordinate marked as each semantic color in the preset color space according to the color coordinate of each pixel point of each sample image in the preset color space and the semantic color marked by each pixel point of each sample image.
And step C, determining a mapping relation according to the number of each semantic color marked by each color coordinate.
In a specific application scenario, a large number of sample images may be collected as a sample image set in a manner of establishing a mapping relationship. Wherein the sample image may be, for example, a photograph taken in the real world, and in order to further improve the accuracy of the mapping relationship, the sample image set may include photographs of each of the plurality of scenes under different lighting conditions. And then, acquiring the color coordinates of each pixel point in each sample image in the preset color space and the semantic color labeled to each pixel point of each sample image, thereby determining the number of each color coordinate labeled to each semantic color in the preset color space. The color coordinates of each pixel point in the preset color space can be automatically identified through the terminal equipment, the semantic color of each pixel point label can be manually labeled, the result of manual labeling is recorded to determine, and the semantic color corresponding to the scene of the real world contained in the sample image can be recorded in advance when the sample image is obtained, so that the semantic color of each pixel point label is determined. Finally, the number of each semantic color marked by each color coordinate can be counted, and the semantic color with the largest number is determined as the semantic color corresponding to the color coordinate, so as to determine the mapping relationship.
For example, if the color coordinates are (128, 128, 50) in the RGB color space, the number of times marked as gray is 1500 times, the number of times marked as blue is 820 times, and the number of times marked as black is 170 times, then gray can be taken as the corresponding semantic color in the RGB color space (128, 128, 50).
In summary, according to the present disclosure, an image to be processed is first identified according to a preset color identification algorithm to obtain a plurality of theme colors, then a theme color meeting a preset condition in the plurality of theme colors is used as a base color, a harmonious color and an inharmonious color of the base color are determined, a theme color belonging to the inharmonious color in the plurality of theme colors is further used as a color to be replaced, and finally, the color to be replaced is replaced according to the harmonious color to obtain a target image. According to the method, the theme color in the image to be processed is firstly identified, and then the color which is not harmonious with the basic color in the theme color is replaced to obtain the target image with harmonious color, so that the effect of beautifying the image is achieved, a large amount of training data does not need to be collected in advance, the image does not need to be beautified manually, the method is simple to realize, the calculated amount is small, and the efficiency of image processing is improved.
Fig. 5 is a block diagram illustrating an apparatus for processing an image according to an exemplary embodiment, and as shown in fig. 5, the apparatus 200 includes:
the obtaining module 201 is configured to obtain a plurality of theme colors of the image to be processed according to a preset color recognition algorithm.
The first determining module 202 is configured to use a theme color meeting a preset condition from the plurality of theme colors as a base color, and determine a harmonious color of the base color and an inharmonious color of the base color.
And the second determining module 203 is used for taking the subject color belonging to the inharmonious color in the plurality of subject colors as the color to be replaced.
And the replacing module 204 is configured to replace the color to be replaced in the image to be processed according to the harmonic color to obtain the target image.
Fig. 6 is a block diagram illustrating another image processing apparatus according to an exemplary embodiment, and as shown in fig. 6, the first determining module 202 includes:
the priority determining sub-module 2021 is configured to determine a priority of each theme color according to an attribute of each theme color in the plurality of theme colors.
The color determination sub-module 2022 is configured to use a preset number of theme colors with the highest priority as the base color.
The color determining sub-module 2022 is further configured to determine a harmonious color and an inharmonious color according to a color relationship table, where the color relationship table includes the harmonious color and the inharmonious color corresponding to each of the plurality of colors.
Optionally, the priority determination sub-module 2021 is configured to perform the following steps:
if the area where the first theme color is located in the image to be processed is the designated object, determining that the priority of the first theme color is the first priority, and the first theme color is any theme color.
And if the area where the first theme color is located in the image to be processed is the salient area, determining the priority of the first theme color as a second priority, wherein the second priority is smaller than the first priority.
Fig. 7 is a block diagram illustrating another image processing apparatus according to an exemplary embodiment, and as shown in fig. 7, the replacement module 204 includes:
the coordinate determination submodule 2041 is configured to obtain a first color coordinate of the harmonic color in the preset color space and a second color coordinate of the color to be replaced in the preset color space.
The replacing submodule 2042 is configured to replace the coordinate value representing chromaticity in the second color coordinate with the coordinate value representing chromaticity in the first color coordinate, so as to obtain a third color coordinate.
The replacing sub-module 2042 is further configured to replace the color to be replaced in the image to be processed with the color indicated by the third color coordinate, so as to obtain the target image.
Fig. 8 is a block diagram illustrating another image processing apparatus according to an exemplary embodiment, and as shown in fig. 8, the obtaining module 201 includes:
the obtaining submodule 2011 is configured to obtain a color coordinate of each pixel point of the image to be processed in the preset color space.
The determining submodule 2012 is configured to determine the semantic color of each pixel according to the mapping relationship between the preset color space and the semantic color and the color coordinate of each pixel.
The determining submodule 2012 is further configured to determine a plurality of theme colors of the image to be processed according to the semantic color of each pixel point.
Wherein the mapping relationship is obtained by the following steps:
step A, a sample image set is obtained, wherein the sample image set comprises a plurality of sample images.
And step B, determining the number of each color coordinate marked as each semantic color in the preset color space according to the color coordinate of each pixel point of each sample image in the preset color space and the semantic color marked by each pixel point of each sample image.
And step C, determining a mapping relation according to the number of each semantic color marked by each color coordinate.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
In summary, according to the present disclosure, an image to be processed is first identified according to a preset color identification algorithm to obtain a plurality of theme colors, then a theme color meeting a preset condition in the plurality of theme colors is used as a base color, a harmonious color and an inharmonious color of the base color are determined, a theme color belonging to the inharmonious color in the plurality of theme colors is further used as a color to be replaced, and finally, the color to be replaced is replaced according to the harmonious color to obtain a target image. According to the method, the theme color in the image to be processed is firstly identified, and then the color which is not harmonious with the basic color in the theme color is replaced to obtain the target image with harmonious color, so that the effect of beautifying the image is achieved, a large amount of training data does not need to be collected in advance, the image does not need to be beautified manually, the method is simple to realize, the calculated amount is small, and the efficiency of image processing is improved.
Referring now to FIG. 9, a block diagram of an electronic device 300 suitable for use in implementing embodiments of the present disclosure is shown. The terminal device in the embodiments of the present disclosure may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a vehicle terminal (e.g., a car navigation terminal), and the like, and a stationary terminal such as a digital TV, a desktop computer, and the like. The electronic device shown in fig. 9 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 9, the electronic device 300 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 301 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)302 or a program loaded from a storage means 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data necessary for the operation of the electronic apparatus 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
Generally, the following devices may be connected to the I/O interface 305: input devices 306 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 307 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage devices 308 including, for example, magnetic tape, hard disk, etc.; and a communication device 309. The communication means 309 may allow the electronic device 300 to communicate wirelessly or by wire with other devices to exchange data. While fig. 9 illustrates an electronic device 300 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication means 309, or installed from the storage means 308, or installed from the ROM 302. The computer program, when executed by the processing device 301, performs the above-described functions defined in the methods of the embodiments of the present disclosure.
It should be noted that the computer readable medium in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the terminal devices, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText transfer protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring a plurality of theme colors of an image to be processed according to a preset color recognition algorithm; taking the theme colors meeting preset conditions in the plurality of theme colors as basic colors, and determining harmonious colors of the basic colors and discordant colors of the basic colors; taking the subject color belonging to the anharmonic color among the plurality of subject colors as a color to be replaced; and replacing the color to be replaced in the image to be processed according to the harmonious color to obtain a target image.
Computer program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including but not limited to an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present disclosure may be implemented by software or hardware. Where the name of a module does not in some cases constitute a definition of the module itself, for example, the second determination module may also be described as a "module that determines a color to be replaced".
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
Example 1 provides a method of processing an image, including: acquiring a plurality of theme colors of an image to be processed according to a preset color recognition algorithm; taking the theme colors meeting preset conditions in the plurality of theme colors as basic colors, and determining harmonious colors of the basic colors and discordant colors of the basic colors; taking the subject color belonging to the anharmonic color among the plurality of subject colors as a color to be replaced; and replacing the color to be replaced in the image to be processed according to the harmonious color to obtain a target image.
Example 2 provides the method of example 1, the taking, as a base color, the theme color satisfying a preset condition among the plurality of theme colors, and determining a harmonious color of the base color and an inharmonic color of the base color, according to one or more embodiments of the present disclosure, including: determining a priority of each theme color according to an attribute of each theme color in a plurality of theme colors; taking the preset number of theme colors with the highest priority as the basic colors; and determining the harmonious color and the inharmonious color according to a color relation table, wherein the color relation table comprises the harmonious color and the inharmonious color corresponding to each color in the plurality of colors.
Example 3 provides the method of example 2, the determining a priority of each of the theme colors according to an attribute of each of the theme colors in the plurality of theme colors, according to one or more embodiments of the present disclosure; if the area where the first theme color is located in the image to be processed is a designated object, determining the priority of the first theme color as a first priority, wherein the first theme color is any theme color; and if the area where the first theme color is located in the image to be processed is a significant area, determining the priority of the first theme color as a second priority, wherein the second priority is smaller than the first priority.
Example 4 provides the method of example 1, wherein replacing the color to be replaced in the image to be processed according to the harmonic color to obtain a target image, according to one or more embodiments of the present disclosure, includes: acquiring a first color coordinate of the harmonious color in a preset color space and a second color coordinate of the color to be replaced in the preset color space; replacing the coordinate value representing the chromaticity in the second color coordinate with the coordinate value representing the chromaticity in the first color coordinate to obtain a third color coordinate; replacing the color to be replaced in the image to be processed with the color indicated by the third color coordinate to obtain the target image.
Example 5 provides the method of example 1, wherein the obtaining of the plurality of theme colors of the image to be processed according to the preset color recognition algorithm includes: acquiring the color coordinates of each pixel point of the image to be processed in a preset color space; determining the semantic color of each pixel point according to the mapping relation between a preset color space and the semantic color and the color coordinate of each pixel point; and determining a plurality of theme colors of the image to be processed according to the semantic color of each pixel point.
Example 6 provides the method of example 5, the mapping relationship being obtained by: obtaining a sample image set, wherein the sample image set comprises a plurality of sample images; determining the number of each color coordinate marked as each semantic color in the preset color space according to the color coordinate of each pixel point of each sample image in the preset color space and the semantic color marked by each pixel point of each sample image; and determining the mapping relation according to the number of each semantic color marked by each color coordinate.
Example 7 provides an apparatus for processing an image, according to one or more embodiments of the present disclosure, including: the acquisition module is used for acquiring a plurality of theme colors of the image to be processed according to a preset color recognition algorithm; the first determining module is used for taking the theme colors meeting preset conditions in the theme colors as basic colors, and determining harmonious colors of the basic colors and discordant colors of the basic colors; a second determination module, configured to use the theme color belonging to the anharmonic color in the plurality of theme colors as a color to be replaced; and the replacing module is used for replacing the color to be replaced in the image to be processed according to the harmonious color so as to obtain a target image.
Example 8 provides the apparatus of example 7, the first determining module comprising: a priority determining submodule for determining a priority of each of the theme colors according to an attribute of each of the theme colors; a color determination submodule configured to use a preset number of theme colors with the highest priority as the base color; the color determining submodule is further configured to determine the harmonious color and the inharmonious color according to a color relationship table, where the color relationship table includes harmonious colors and inharmonious colors corresponding to each of the plurality of colors.
Example 9 provides a computer readable medium having stored thereon a computer program that, when executed by a processing apparatus, implements the steps of the methods of examples 1-6, in accordance with one or more embodiments of the present disclosure.
Example 10 provides, in accordance with one or more embodiments of the present disclosure, an electronic device comprising: a storage device having a computer program stored thereon; processing means for executing the computer program in the storage means to implement the steps of the methods of examples 1-6.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the disclosure herein is not limited to the particular combination of features described above, but also encompasses other embodiments in which any combination of the features described above or their equivalents does not depart from the spirit of the disclosure. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.
Further, while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims. With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
Claims (10)
1. A method of processing an image, the method comprising:
acquiring a plurality of theme colors of an image to be processed according to a preset color recognition algorithm;
taking the theme colors meeting preset conditions in the plurality of theme colors as basic colors, and determining harmonious colors of the basic colors and discordant colors of the basic colors;
taking the subject color belonging to the anharmonic color among the plurality of subject colors as a color to be replaced;
and replacing the color to be replaced in the image to be processed according to the harmonious color to obtain a target image.
2. The method according to claim 1, wherein the step of taking the theme colors satisfying a preset condition from among the plurality of theme colors as base colors and determining harmonious colors of the base colors and discordant colors of the base colors comprises:
determining a priority of each theme color according to an attribute of each theme color in a plurality of theme colors;
taking the preset number of theme colors with the highest priority as the basic colors;
and determining the harmonious color and the inharmonious color according to a color relation table, wherein the color relation table comprises the harmonious color and the inharmonious color corresponding to each color in the plurality of colors.
3. The method according to claim 2, wherein said determining a priority of each of said theme colors according to an attribute of each of said theme colors;
if the area where the first theme color is located in the image to be processed is a designated object, determining the priority of the first theme color as a first priority, wherein the first theme color is any theme color;
and if the area where the first theme color is located in the image to be processed is a significant area, determining the priority of the first theme color as a second priority, wherein the second priority is smaller than the first priority.
4. The method according to claim 1, wherein the replacing the color to be replaced in the image to be processed according to the harmonious color to obtain a target image comprises:
acquiring a first color coordinate of the harmonious color in a preset color space and a second color coordinate of the color to be replaced in the preset color space;
replacing the coordinate value representing the chromaticity in the second color coordinate with the coordinate value representing the chromaticity in the first color coordinate to obtain a third color coordinate;
replacing the color to be replaced in the image to be processed with the color indicated by the third color coordinate to obtain the target image.
5. The method according to claim 1, wherein the obtaining a plurality of theme colors of the image to be processed according to a preset color recognition algorithm comprises:
acquiring the color coordinates of each pixel point of the image to be processed in a preset color space;
determining the semantic color of each pixel point according to the mapping relation between a preset color space and the semantic color and the color coordinate of each pixel point;
and determining a plurality of theme colors of the image to be processed according to the semantic color of each pixel point.
6. The method of claim 5, wherein the mapping relationship is obtained by:
obtaining a sample image set, wherein the sample image set comprises a plurality of sample images;
determining the number of each color coordinate marked as each semantic color in the preset color space according to the color coordinate of each pixel point of each sample image in the preset color space and the semantic color marked by each pixel point of each sample image;
and determining the mapping relation according to the number of each semantic color marked by each color coordinate.
7. An apparatus for processing an image, the apparatus comprising:
the acquisition module is used for acquiring a plurality of theme colors of the image to be processed according to a preset color recognition algorithm;
the first determining module is used for taking the theme colors meeting preset conditions in the theme colors as basic colors, and determining harmonious colors of the basic colors and discordant colors of the basic colors;
a second determination module, configured to use the theme color belonging to the anharmonic color in the plurality of theme colors as a color to be replaced;
and the replacing module is used for replacing the color to be replaced in the image to be processed according to the harmonious color so as to obtain a target image.
8. The apparatus of claim 7, wherein the first determining module comprises:
a priority determining submodule for determining a priority of each of the theme colors according to an attribute of each of the theme colors;
a color determination submodule configured to use a preset number of theme colors with the highest priority as the base color;
the color determining submodule is further configured to determine the harmonious color and the inharmonious color according to a color relationship table, where the color relationship table includes harmonious colors and inharmonious colors corresponding to each of the plurality of colors.
9. A computer-readable medium, on which a computer program is stored, characterized in that the program, when being executed by processing means, carries out the steps of the method of any one of claims 1 to 6.
10. An electronic device, comprising:
a storage device having a computer program stored thereon;
processing means for executing the computer program in the storage means to carry out the steps of the method according to any one of claims 1 to 6.
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