Shen et al., 2007 - Google Patents
Capture local information in shape representationShen et al., 2007
- Document ID
- 8386931923957569946
- Author
- Shen H
- Zhou X
- Publication year
- Publication venue
- Multimedia Tools and Applications
External Links
Snippet
Research in content-based image retrieval has been around for over a decade. While the research community has successfully exploited content features such as color and texture, finding an effective shape representation and measure remains a challenging task. The …
- 238000000034 method 0 abstract description 15
Classifications
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- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
- G06K9/52—Extraction of features or characteristics of the image by deriving mathematical or geometrical properties from the whole image
- G06K9/527—Scale-space domain transformation, e.g. with wavelet analysis
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6201—Matching; Proximity measures
- G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
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- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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- G06K9/4671—Extracting features based on salient regional features, e.g. Scale Invariant Feature Transform [SIFT] keypoints
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- G06F17/30244—Information retrieval; Database structures therefor; File system structures therefor in image databases
- G06F17/30247—Information retrieval; Database structures therefor; File system structures therefor in image databases based on features automatically derived from the image data
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- G06K9/62—Methods or arrangements for recognition using electronic means
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- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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- G—PHYSICS
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