JP3564216B2 - Image processing device - Google Patents

Description

【００２３】
注目画素を含んで周辺データが閾値ｔｈｗ より小さい時、白領域とする。このパターンは直交パターンであるが、斜めなどのパターンを追加してもよい。
【００２４】
黒画素検出において、十分に濃い画素を黒画素とする。式で表すとａ_２２＞ｔｈＢとなる。エッヂ量抽出において、５×５のマトリックスで、次のようにエッヂ量を求める。
【００２５】
ｘ ＝ （ａ_２２×２） −（ａ_２１＋ａ_２３）
ｙ ＝（ａ_２２×２） −（ａ_１２＋ａ_３２）
ｚ ＝ ｉ×ｘ ＋ ｊ×ｙ
但し、ｘは、主走査方向のエッヂ量、
ｙは、副走査方向のエッヂ量、
ｚは、ｘ、ｙに重みづけをして、総エッヂ量を求める。
【００２６】
ここで、ｉ、ｊ＝とも、選択的な係数で、ハードウェアを設計する際に、ゲート規模が小さくなるような係数、１、１．１１５、１．２５、１．３７５、１．５、１．６２５、１．７５、１．８７５、２にしている（固定小数点演算）。このようにしておくことにより、主走査と副走査のＭＴＦ（光学系と、走行系）などのぼけを修正する。
【００２７】
一般に主走査と副走査のＭＴＦは異なっており、さらに副走査の変倍は、読み取り装置の読み取り面積により行なっているため、副走査の変倍率によりＭＴＦは異なる。本実施形態は、主走査変倍は、原稿認識部のあとなので気にする必要はない。さらに、副走査の倍率が大きい時、例えば、２００％の時は、次のようにエッヂ量を求めるように選択可能である。
【００２８】
ｘ ＝（ａ_２２×２） −（ａ_２０＋ａ_２４）
ｙ ＝（ａ_２２×２） −（ａ_０２＋ａ_４２）
ｚ ＝ ｉ×ｘ ＋ ｊ×ｙ
【００２９】
このようにすることにより、副走査の変倍処理に対応している。出力は白領域信号と、黒画素、信号とエッヂ量を出力する。白領域信号は、Ｈで白領域を示し、黒画素信号は、Ｈで黒画素を示す。
【００３０】
図６は、線画の断面図であり、白領域と黒画素と閾値と関係を表す概念図である。また、図７はエッヂ量（ｚ）の関係を表す図である。
【００３１】
次にパターンマッチング部Ａ、Ｂ、Ｃを説明する。
パターンマッチング部Ａ４３のブロックでは、白領域周辺の黒エッヂを抽出する。ここで白領域パターン（Ｗ）は、白領域の信号であり、黒パターン（Ｋ）は、黒画素、または、エッヂ量が閾値ｔｈＲＢ より、大きいものをＨとする。黒パターンは単純に黒画素で抽出を行なわないのは、原稿読み取り時のボケをエッヂ量で補正するものである。概念図は、図６、図７に示してある。パターン例としては、次式の（７×７）のようになる。
【００３２】

【００３３】
水平成分、垂直成分のみで示したが、同様に、ななめ成分のパターンも同様に抽出する。このように白領域上のエッヂを抽出する。白領域が多いので網点を線画と誤認識することなく、白領域の線画を抽出が可能となる。
【００３４】
パターンマッチング部Ｂ４４のブロックでは、細線の検出を行なう。細線とは、文書中のケイ線や、文字などが該当する。ここで白パターン（ｗ）は、白領域であるか、または、エッヂ量が閾値 ｔｈＲｗ より小さい（マイナス成分なので、絶対値は大きい） ものをＨとする。黒パターン（ｋ） は、黒画素または、エッ
ヂ量が閾値 ｔｈＲＢ より大きいものをＨとする。ここのｔｈＲＢは、パターンマッチング部Ｃ４５とは同じである必要はない。黒パターン、白パターンともエッヂ量成分で補正するのは、細線のコントラストをあげている。
パターンの例としては、次式の（７×７）のようになる。
【００３５】

【００３６】
水平成分、垂直成分のみで示したが、同様に、ななめ成分のパターンも同様に抽出する。このように黒パターンの両側を、白パターンではさみこまれている場合に、細線として抽出する。また、白領域が存在する時には、線画である可能性が高いので、パターンマッチングをあまくしてもよい。例えば、次式のようになる。白領域を記号ａとする。
【００３７】

【００３８】
などを追加してもよい。ここでは水平成分のみ示したが、同様に垂直成分、斜め成分も同様に抽出する。さらに、このパターンと逆に白パターンの両側を、白パターンではさみ込まれている場合には、細線であるので、このようなパターンで追加してもよいし、白パターンを中心としたパターンマッチングでもよい。
【００３９】
パターンマッチング部Ｃ４５のブロックは、パターンマッチング部Ａ４３の補助的なもので、白領域上の黒エッヂを抽出するために、白エッヂ成分の３つ要素でパターンマッチングを行なう。ここで白領域パターン（ａ）は、白領域の信号であり、黒パターン（ｋ） は、黒画素、または、エッヂ量が閾値 ｔｈＲＢ より大きいものをＨとする。白パターン（ｗ）は、白領域であるか、またはエッヂ量が閾値 ｔｈＲｗ より小さい（マイナス成分なので、絶対値は大きい）ものをＨとする。パターンの例としては、次式の（７×７）のようになる。
【００４０】

【００４１】
ここでは、水平成分のみ示したが、同様に、垂直・水平成分のみ示したが、同様に斜め成分も同様に抽出する。このことにより、コントラストのしっかりした文字を抽出することが、可能となる。そして、白エッヂ成分を検出している分、黒パターンの幅を少なくしても網点を誤検知することなく、小さな文字などが抽出可能となる。ここでの閾値、ｔｈＲＢ、ｔｈＲｗ に、同一でなくてもよい。本実施例は、７×７で行なったが、マトリックスサイズは、何でもよい。さらに、パターンマッチング部Ａ、Ｂ、Ｃのマトリックスを成分する際には、ラインメモリを用いるが、独立に行なうのではなく、共有してもよい。
【００４２】
例としては、ｔｈｗ 、ｔｈｋ が同一であるならば、共有可能であるし、大小関
係を利用してコード化してもかまわない。コード化の例として、下記を掲げる。
【００４３】
パターン２の ｔｈＲｗ を、 ｔｈＲｗ_２ 、 ｔｈＲＢ を、ｔｈＲＢ_２
パターン３の ｔｈＲｗ を、 ｔｈＲｗ_３ 、 ｔｈＲＢ を、ｔｈＲＢ_３
【００４４】
ここにおいて、大小関係が、
ｔｈＲｗ_２ ＞ ｔｈＲｗ_３ ＞ ｔｈＲＢ_３ ＞ ｔｈＲＢ_２ ＞ ｔｈＲＢ_３
ならば、通常、５ｂｉｔ×ｎラインとなるが、コードを次のようにすると、３ｂｉｔ
×ｎラインとなる。
【００４５】

【００４６】
ここでＰは、エッヂ量である。コードは、０〜５であるので、３ｂｉｔあれば表現できる。コードを展開する時に、逆に行なえばよい。大小関係は、固定でなくても入れかえられるようにした方がよいのはいうまでもない。孤立点除去において、線画は連続した線からなるので、孤立点を除去する。孤立点は、網点を線画と誤検出した場合に生じる。
【００４７】
パターンマッチング部Ａ４３、パターンマッチング部Ｂ４４、パターンマッチング部Ｃ４５のいずれか一つ以上で抽出したら抽出パターンとする。例えば、５×５のパターンマッチングにおいて、周辺画素に抽出パターンがなく、注目画素に注目画素が抽出パターンならば除去する。一例を式で示す。ここにおいて、抽出パターンを記号ａとする。
【００４８】
【外１】

【００４９】
また、パターンマッチングでなく、マトリックス内の数をかぞえて判定してもよい。
【００５０】
膨張部４７において、抽出パターンを膨張することにより、文字の交点などをつなぎ、さらに線画とその周辺を線画処理を行なうようにする。
【００５１】
上述のパターンマッチングは、十字の交点を抽出できないが、連結が可能となる。また、線画とその周辺を線画とみなすのは、黒文字処理と空間フィルタを良好に作用させるためである。次式に例（７×７）を示す。
【００５２】

【００５３】
このことにより、印刷原稿の線画を良好に抽出可能とする。これは等倍の例であり、変倍について説明する。図８および図９は線画の抽出手順を説明するための概念図であり、図中の実線が線画、点線が線画認識部であり線画として判定する領域を表している。
【００５４】
副走査変倍は、原稿認識の前（原稿読み取り部１１）で行なっており、主走査変倍は、原稿認識の後（変倍部２６）で行なっている。このことにより、例えば等倍で処理した時、図９のように主・副走査とも同じ幅で線画処理を行なうが、主・副走査とも２００％で処理をすると、図８のように主走査のみ線画処理を行なう幅が大きくなる。よって主走査の変倍率により、主走査の膨張幅を変える。式の構成例を以下に示す。
【００５５】
（（膨張量−１）／２／変倍率）×２＋１
つまり、
（７−１）／２／２×２＋１＝ ４．５
【００５６】
膨張量は、整数でなければならないので、５とする。このことにより、変倍率の影響により、主走査と副走査の線処理の処理範囲がほぼ同一の幅となる。逆に主走査の変倍率により、副走査の膨張幅をかえても同様の効果がある。式の構成例を以下に示す。
【００５７】
（（膨張量−１）／２×変倍率）×２＋１）
【００５８】
本実施形態は、輪郭抽出するものすべてに適用できる。さらに、孫コピー（ジェネレーション、複写機の出力を入力原稿として複写）する際には、上述のパラメータを印刷原稿と異なる。パラメータ（ｔｈｗ、ｔｈＢ、ｔｈＲｗ、ｔｈＲＢ） を変更するほかに、パターンマッチング部Ｃ４５の抽出動作を行なわないようにする。
【００５９】
現在の複写機の出力は、文字を４００ＤＰＩ写真部が、２００ＤＰＩの万線パターンが一般的である。万線パターンは線画と誤検出しやすいので、パターンマッチング部Ｃ４５の抽出動作を行なわないようにする。複写機は印刷物に対して、１／１０程度の解像度なので、孫コピーにはさほど影響しない。このように解像度の低い原稿（孫コピー）に対しては、良好に抽出可能となる。
【００６０】
【発明の効果】
以上の説明より明かなように、本発明の画像処理装置は、副走査を副走査変倍率で変倍し、主走査を主走査変倍率で変倍し、副走査変倍率と主走査変倍率に応じて輪郭抽出の結果を膨張する。よって、主走査変倍率により主走査又は副走査の輪郭の膨張量を変えることにより、出力結果を変倍率に影響なくほぼ一定にすることができる。
【図面の簡単な説明】
【図１】本発明の画像処理装置の実施例を示す主要構成ブロック図である。
【図２】図１の画像処理部の構成例を示すブロック図である。
【図３】図２の原稿認識部の構成例を示すブロック図である。
【図４】図３の線画認識部の構成例を示すブロック図である。
【図５】白領域検出の動作を説明するための記号化されたマトリックスである。
【図６】線画の概念的な断面図であり、白領域と黒画素と閾値とを表している。
【図７】線画の概念的な断面図であり、エッジ量と閾値とを表している。
【図８】印刷原稿の線画の抽出手順を説明するための概念図１である。
【図９】印刷原稿の線画の抽出手順を説明するための概念図２である。
【符号の説明】
１１ 原稿読み取り部
１２ 画像処理部
１３ 画像記録部
２１ ＲＧＢγ補正部
２２ 遅延部
２３ ＲＧＢフィルタ部
２４ 色補正部
２５ ＶＣＲ部
２６ 変倍部
２７ ＣＭＹＢｋフィルタ部
２８ ＣＭＹＢｋγ補正部
２９ 階調処理部
３０ 原稿認識部
３１ 線画認識部
３２ 色判定部
４１ モノクロ化部
４２ ラプラシアン部
４３、４４、４５ パターンマッチング部
４６ 孤立点除去部
４７ 膨張部[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to an image processing apparatus, and more particularly, to an image processing apparatus that extracts an edge of a line drawing (character) with reference to a plurality of pixels, switches parameters according to the result, and performs an image forming process.
[0002]
[Prior art]
2. Description of the Related Art Conventionally, there is an image processing apparatus that can change a parameter for determining the edge of a line drawing in accordance with a magnification. The reason for providing this function is that the characteristics of the image data of the reading unit change according to the magnification.
[0003]
For the same reason, some image processing apparatuses change the image processing filter. For example, in an apparatus that reads image data by scanning four times, the main scanning magnification of a component may be arranged after the document recognition unit, and the sub-scan magnification may be arranged before the document recognition unit.
[0004]
[Problems to be solved by the invention]
However, in the image processing apparatus having the arrangement configuration as in the conventional example described above, since the edge (outline) of the line as a result of the document recognition unit is extracted by the magnification, the width of the main scan and the sub-scan is output as the output result. different. In addition, if the main scanning magnification is arranged before the document recognition unit, there is a problem that three circuit units for R, G, and B are required.
[0005]
SUMMARY OF THE INVENTION It is an object of the present invention to provide an image processing apparatus that makes the output results of edge detection substantially constant even when the magnification of main scanning and sub-scanning are changed.
[0006]
[Means for Solving the Problems]
In order to achieve the above object, the present invention provides a document reading unit that reads a document and outputs it as digital data, an image processing unit that corrects image data read by the document reading unit and performs document recognition, An image recording unit that outputs the output image data of the document to a sheet, wherein the image processing unit includes a line drawing recognizing unit that recognizes the likeness of the line drawing and a specific area of the document being chromatic or achromatic. A document recognizing section comprising a color determining section for determining whether or not the image data has been enlarged and reduced in the main scanning direction or a magnification changing section for performing equal magnification processing. The line drawing recognizing section converts the RGB data into a monochrome signal. , A Laplacian section that extracts the edges of line drawings and detects white areas and black pixels, and a pattern match that extracts black edges around white areas and detects thin lines And a dilation unit that expands the extracted pattern from the pattern matching unit to connect the intersections of the characters and performs line drawing processing and line drawing processing around the line drawing. The magnification in the main scanning direction is executed in the original reading unit, which is a pre-processing stage for performing original recognition in the unit, and the magnification in the main scanning direction is a post-processing stage of the original recognition unit in which the line image recognition and the color determination are performed. And the expansion width in the main scanning direction or the sub-scanning direction is changed according to the magnification in the main scanning direction.
[0008]
BEST MODE FOR CARRYING OUT THE INVENTION
Next, an embodiment of an image processing apparatus according to the present invention will be described in detail with reference to the accompanying drawings. 1 to 7 show an embodiment of an image processing apparatus according to the present invention. FIG. 1 is a block diagram of a main configuration of an image processing apparatus, FIGS. 2 to 4 are block diagrams of an internal partial configuration, FIG. 5 is a matrix for explaining an operation of white area detection, and FIGS. FIGS. 8 and 9 are conceptual views for explaining a procedure for extracting a line drawing of a print original.
[0009]
As shown in FIG. 1, the image processing apparatus reads a document, outputs a read data as digital data, a document reading unit 11, an image processing unit 12 that corrects image data read by the document reading unit 11 and performs document recognition, An image recording unit 13 outputs the output image data of the image processing unit 12 to a sheet.
[0010]
The image processing unit 12, which is a main part of the present embodiment, will be described with reference to FIG.
The RGB γ correction unit 21 corrects the gray balance of the RGB data and converts the RGB data into density data.
[0011]
The delay unit 22 delays the RGB data in order to synchronize with the output result of the document recognition unit 30. The document recognizing unit 30 determines a character area or a picture area according to the RGB image data, and outputs a C / P signal to the RGB filter unit 23. The logic of the C / P signal is H for characters and L for pictures.
[0012]
Further, it determines whether the document area is a chromatic area or an achromatic area, and outputs a B / C signal to the RGB filter unit 23. The logic of the B / C signal is an achromatic region at H and a chromatic region at L. The C / P signal is cascaded to an RGB filter unit 23, a color correction unit 24, a VCR unit 25, a scaling unit 26, a CMYBk filter unit 27, a CMYBkγ correction unit 28, and a gradation processing unit 29, and is synchronized with image data. And outputs a signal IMG.
[0013]
Each block switches between character processing and picture processing according to the C / P signal and the B / C signal. The B / C signal is cascade-connected to an RGB filter unit 23, a color correction unit 24, and a VCR unit 25, and outputs the B / C signal in synchronization with image data.
[0014]
The RGB filter unit 23 is a filter for performing MTF correction on RGB data and is configured by an N × N matrix. When the C / P signal is H, sharpening processing is performed, and when it is L, smoothing processing is performed. The color correction unit 24 converts the RGB data into C, M, Y data by primary masking or the like.
[0015]
The VCR unit 25 expresses the image data in four colors C, M, Y, and Bk in order to improve the color reproduction of the image data. The common portion of C, M, Y is subjected to VCR (additional color removal) to generate Bk data. When the C / P signal is L, skeleton black Bk is generated. When the C / P signal is H, full black processing is performed. Further, when the C / P signal is H and the B / C signal is H, the C, M, Y data is erased. This is because black characters are represented only by black components. Further, the output IMG is a one-color sequential image that outputs one color among C, M, Y, and Bk. That is, by reading the document four times, full color (four colors) data is created.
[0016]
The scaling unit 26 performs enlargement / reduction in the main scanning direction or equal magnification processing. The CMYBk filter unit 27 performs a smoothing process and a sharpening process using an NXN spatial filter according to the frequency characteristics of the image recording unit 13 and the C / P signal. The CMYBkγ correction unit 28 performs processing by changing the γ curve according to the frequency characteristics of the image recording unit 13 and the C / P signal. When the C / P signal is "L", the contrast is emphasized by using γ which faithfully reproduces the image, and when the C / P signal is "H", γ is added.
[0017]
The gradation processing unit 29 performs quantization such as dither processing according to the gradation characteristics of the image recording unit 13 and the C / P signal. When the C / P signal is "L", a process that emphasizes gradation is performed, and when the C / P signal is "H", a process that emphasizes resolution is performed. Further, as shown in FIG. 3, the document recognizing unit 30 includes a line drawing recognizing unit 31 for detecting the likeness of a line drawing, and a color determining unit 32 for determining whether a specific area of the document is chromatic or achromatic.
[0018]
The output logic of the C / P signal of the line drawing recognition unit 31 outputs “H” when the edge of the line drawing is reached, and outputs “L” otherwise. In addition, the B / C signal output logic of the color determination unit 32 outputs “L” in a chromatic region, and outputs “H” in other cases. The output result is a signal in which 4 × 4 pixels correspond to one pixel. In the following, the unit of the output result is one block.
[0019]
In the present embodiment, a document reading unit having a reading density of about 400 DPI will be described as an example. The line drawing recognition unit 31 which is a main part of the present embodiment will be described with reference to FIG. 4, the line image recognition unit 31 includes a monochrome unit 41, a Laplacian unit 42, Y pattern matching units A, B, and C (43 to 45), an isolated point removal unit 46, and an expansion unit 47.
[0020]
The monochrome conversion section 41 converts the RGB data into luminance data or the like to generate a monochrome signal. For example, instead of the luminance data, the darkest data among R, G, and B may be selected, or G may be used as the luminance data. The output data indicates that the larger the number, the higher the density, and the smaller the number, the lower the level.
[0021]
The Laplacian unit 42 detects the white area and the black pixels at the same time as extracting the edge of the line drawing. By detecting a white region, the data is used as data for extracting a line drawing on a white background. The operation of white area detection will be described with reference to the symbolized matrix of FIG. For example, assuming that the matrix of the white area is 3 × 3, the following is obtained.
[0022]

[0023]
When the peripheral data including the target pixel is smaller than the threshold value thw, the white area is set. This pattern is an orthogonal pattern, but an oblique pattern or the like may be added.
[0024]
In black pixel detection, a sufficiently dark pixel is defined as a black pixel. In a formula, a ₂₂ > thB. In the edge amount extraction, the edge amount is obtained as follows using a 5 × 5 matrix.
[0025]
_{x = (a 22 × 2)} - (a 21 + a 23)
_{y = (a 22 × 2)} - (a 12 + a 32)
z = ixx + jxy
Here, x is the edge amount in the main scanning direction,
y is the edge amount in the sub-scanning direction,
As for z, x and y are weighted to determine the total edge amount.
[0026]
Here, i and j = are both selective coefficients and are coefficients that reduce the gate scale when designing hardware, 1, 1.115, 1.25, 1.375, 1.5, 1.625, 1.75, 1.875, and 2 (fixed point arithmetic). By doing so, blurring of the MTF (optical system and traveling system) of the main scanning and the sub-scanning is corrected.
[0027]
Generally, the MTFs of the main scanning and the sub-scanning are different, and the magnification of the sub-scanning is performed by the reading area of the reading device. In the present embodiment, since the main scanning magnification change is performed after the document recognition unit, there is no need to worry. Further, when the sub-scanning magnification is large, for example, when the magnification is 200%, it is possible to select the edge amount as follows.
[0028]
_{x = (a 22 × 2)} - (a 20 + a 24)
_{y = (a 22 × 2)} - (a 02 + a 42)
z = ixx + jxy
[0029]
In this way, it is possible to cope with the magnification change processing of the sub-scan. The output outputs a white area signal, a black pixel, a signal and an edge amount. The white area signal indicates a white area with H, and the black pixel signal indicates a black pixel with H.
[0030]
FIG. 6 is a cross-sectional view of a line drawing, and is a conceptual diagram illustrating a relationship between a white region, a black pixel, and a threshold. FIG. 7 is a diagram showing the relationship between the edge amount (z).
[0031]
Next, the pattern matching units A, B, and C will be described.
In the block of the pattern matching unit A43, a black edge around the white area is extracted. Here, the white area pattern (W) is a signal of the white area, and the black pattern (K) is H when a black pixel or an edge amount is larger than the threshold thRB. The reason why the black pattern is not simply extracted with black pixels is to correct the blur at the time of reading the original with the edge amount. The conceptual diagrams are shown in FIGS. An example of the pattern is as follows (7 × 7).
[0032]

[0033]
Although only the horizontal component and the vertical component are shown, the pattern of the slant component is similarly extracted. Thus, the edge on the white area is extracted. Since there are many white areas, a line image of a white area can be extracted without erroneously recognizing a halftone dot as a line image.
[0034]
In the block of the pattern matching unit B44, a thin line is detected. A thin line corresponds to a key line or a character in a document. Here, the white pattern (w) is a white area or an H whose edge amount is smaller than the threshold thRw (absolute value is large because it is a negative component). The black pattern (k) is defined as H when a black pixel or an edge amount is larger than the threshold thRB. The thRB here need not be the same as that of the pattern matching unit C45. Correcting both the black pattern and the white pattern with the edge amount component increases the contrast of the fine line.
An example of the pattern is as follows (7 × 7).
[0035]

[0036]
Although only the horizontal component and the vertical component are shown, the pattern of the slant component is similarly extracted. As described above, when both sides of the black pattern are sandwiched by the white pattern, they are extracted as thin lines. Further, when a white area exists, it is highly possible that the image is a line drawing, so that pattern matching may be performed. For example, Let the white area be a symbol a.
[0037]

[0038]
Etc. may be added. Although only the horizontal component is shown here, the vertical component and the oblique component are similarly extracted. Further, in contrast to this pattern, when both sides of the white pattern are sandwiched by the white pattern, the pattern is a thin line. Therefore, such a pattern may be added. May be.
[0039]
The block of the pattern matching unit C45 is auxiliary to the pattern matching unit A43, and performs pattern matching using three elements of a white edge component in order to extract a black edge on a white area. Here, the white area pattern (a) is a signal of the white area, and the black pattern (k) is H when a black pixel or an edge amount is larger than the threshold thRB. The white pattern (w) is a white area or an H whose edge amount is smaller than the threshold thRw (the absolute value is large because it is a negative component). An example of the pattern is as follows (7 × 7).
[0040]

[0041]
Although only the horizontal component is shown here, only the vertical and horizontal components are shown, but the diagonal components are similarly extracted. As a result, it is possible to extract characters having a high contrast. Then, even if the width of the black pattern is reduced, a small character or the like can be extracted without erroneously detecting a halftone dot, because the white edge component is detected. The threshold values, thRB, thRw, need not be the same. In this embodiment, the matrix is 7 × 7, but the matrix size is not limited. Further, when the matrixes of the pattern matching units A, B, and C are used as components, a line memory is used, but may be shared instead of independently.
[0042]
As an example, if thw and thk are the same, they can be shared and may be coded using a magnitude relationship. The following are examples of coding.
[0043]
The thRw of the pattern 2 is represented by thRw ₂ , thRB, and thRB ₂
In pattern 3, thRw, thRw ₃ , thRB, thRB ₃
[0044]
Here, the magnitude relationship is
_{thRw 2> thRw 3> thRB 3} > thRB 2> thRB 3
Then, it is usually 5 bits x n lines, but if the code is as follows, 3 bits
× n lines.
[0045]

[0046]
Here, P is an edge amount. Since the code is from 0 to 5, it can be expressed with 3 bits. When developing the code, you can do the reverse. Needless to say, it is better to exchange the magnitude relation even if it is not fixed. In the isolated point removal, since the line image is composed of continuous lines, the isolated points are removed. An isolated point occurs when a halftone dot is erroneously detected as a line image.
[0047]
If any one or more of the pattern matching unit A43, the pattern matching unit B44, and the pattern matching unit C45 extracts the pattern, the extracted pattern is set. For example, in 5 × 5 pattern matching, if there is no extracted pattern in the surrounding pixels and the target pixel is the extracted pattern, the target pixel is removed. An example is shown by a formula. Here, the extracted pattern is represented by a symbol a.
[0048]
[Outside 1]

[0049]
Also, instead of pattern matching, the determination may be made by counting the numbers in the matrix.
[0050]
The expansion unit 47 expands the extracted pattern to connect the intersections of the characters and to perform the line drawing processing on the line drawing and its surroundings.
[0051]
In the above-mentioned pattern matching, intersections of crosses cannot be extracted, but connection is possible. The reason why a line drawing and its surroundings are regarded as a line drawing is to make black character processing and a spatial filter work well. The following equation shows an example (7 × 7).
[0052]

[0053]
This makes it possible to satisfactorily extract a line image of a printed document. This is an example of the same magnification, and the magnification will be described. FIG. 8 and FIG. 9 are conceptual diagrams for explaining the line drawing extraction procedure, in which solid lines in the drawings indicate a line drawing, and dotted lines indicate a line drawing recognizing unit and an area determined as a line drawing.
[0054]
The sub-scanning magnification is performed before document recognition (document reading unit 11), and the main scanning magnification is performed after document recognition (magnification unit 26). Thus, for example, when processing is performed at the same magnification, line drawing processing is performed with the same width in both main and sub-scanning as shown in FIG. 9, but when processing is performed at 200% in both main and sub-scanning, as shown in FIG. Only the line drawing process becomes wider. Therefore, the expansion width of the main scan is changed according to the magnification of the main scan. A configuration example of the expression is shown below.
[0055]
((Expansion amount-1) / 2 / magnification) × 2 + 1
That is,
(7-1) /2/2×2+1=4.5
[0056]
Since the expansion amount must be an integer, it is set to 5. As a result, the processing ranges of the line processing in the main scanning and the sub-scanning have substantially the same width due to the influence of the magnification. Conversely, the same effect is obtained even if the expansion width of the sub-scan is changed by changing the magnification of the main scan. A configuration example of the expression is shown below.
[0057]
((Expansion amount -1) / 2 x magnification) x 2 + 1)
[0058]
The present embodiment can be applied to all contour extraction. Further, when the grandchild copy (generation, copying the output of the copying machine as an input document), the above-described parameters are different from those of the print document. In addition to changing the parameters (thw, thB, thRw, thRB), the extraction operation of the pattern matching unit C45 is not performed.
[0059]
The current output of a copying machine is generally a 400 DPI photo part for characters and a 200 DPI line pattern. Since the line pattern is easily erroneously detected as a line drawing, the extraction operation of the pattern matching unit C45 is not performed. Since the copier has a resolution of about 1/10 of the printed matter, it does not significantly affect the grandchild copy. As described above, it is possible to satisfactorily extract a low-resolution original (a grandchild copy).
[0060]
【The invention's effect】
As is clear from the above description, the image processing apparatus according to the present invention changes the magnification of the sub-scan at the sub-scan magnification, the magnification of the main scan at the main scan magnification, the sub-scan magnification, and the main scan magnification. Expands the result of the contour extraction according to. Therefore, by changing the expansion amount of the main scanning or sub-scanning contour according to the main scanning magnification, the output result can be made substantially constant without affecting the magnification.
[Brief description of the drawings]
FIG. 1 is a main configuration block diagram illustrating an embodiment of an image processing apparatus according to the present invention.
FIG. 2 is a block diagram illustrating a configuration example of an image processing unit in FIG. 1;
FIG. 3 is a block diagram illustrating a configuration example of a document recognition unit in FIG. 2;
FIG. 4 is a block diagram illustrating a configuration example of a line drawing recognition unit in FIG. 3;
FIG. 5 is a symbolized matrix for explaining the operation of white area detection.
FIG. 6 is a conceptual cross-sectional view of a line drawing, showing a white area, a black pixel, and a threshold.
FIG. 7 is a conceptual cross-sectional view of a line drawing, showing an edge amount and a threshold.
FIG. 8 is a conceptual diagram for explaining a procedure for extracting a line image of a print original.
FIG. 9 is a conceptual diagram for explaining a procedure for extracting a line image of a print document.
[Explanation of symbols]
REFERENCE SIGNS LIST 11 original reading unit 12 image processing unit 13 image recording unit 21 RGB γ correction unit 22 delay unit 23 RGB filter unit 24 color correction unit 25 VCR unit 26 scaling unit 27 CMYBk filter unit 28 CMYBk γ correction unit 29 gradation processing unit 30 document recognition Unit 31 line drawing recognition unit 32 color determination unit 41 monochrome unit 42 Laplacian units 43, 44, 45 pattern matching unit 46 isolated point removal unit 47 expansion unit

Claims (1)

A document reading unit that reads a document and outputs it as digital data; an image processing unit that corrects image data read by the document reading unit and performs document recognition; and an image recording unit that outputs output image data of the image processing unit to a sheet And an image processing apparatus comprising:
The image processing unit includes: a document recognition unit including a line drawing recognition unit for recognizing the likeness of a line drawing and a color determination unit for determining whether a specific region of the document is chromatic or achromatic; an enlargement / reduction or equal magnification process in the main scanning direction And a scaling unit for performing
The line drawing recognizing unit converts the RGB data into a monochrome signal and outputs a monochrome signal. The line drawing recognizing unit extracts the edges of the line drawing and detects the white area and black pixels. The line drawing recognizing unit extracts the black edge around the white area. A pattern matching unit that detects a thin line, and an expansion unit that connects the intersection of characters by expanding an extraction pattern from the pattern matching unit, and performs a line drawing and a line drawing process around the line drawing,
Zooming in the sub-scanning direction is performed in the document reading unit, which is a pre-processing stage for performing document recognition in the image processing unit,
The scaling in the main scanning direction is performed in the scaling unit, which is a post-processing stage of the line recognition and the color-recognized document recognition unit,
An image processing apparatus wherein an expansion width in a main scanning direction or a sub-scanning direction is changed according to a magnification in a main scanning direction.

Images