Non-linear quantization and similarity matching methods for retrieving image data

An image and image block technology, applied in the direction of image data processing, image data processing, electrical digital data processing, etc.
CN1470131AInactive Publication Date: 2004-01-21ELECTRONICS & TELECOMM RES INST
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
ELECTRONICS & TELECOMM RES INST
Publication Date
2004-01-21
Estimated Expiration
Not applicable Β· inactive patent

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Abstract

A method for constructing a database having image information representing a plurality of images including the steps of: a) calculating Lx5 number of normalized edge histogram bins to generate L number of edge histograms of a target image, wherein each edge histogram has five normalized edge histogram bins and represents a spatial distribution of five reference edges in a sub-image and L is a positive integer, wherein the reference edges include four directional edges and a non-directional edge; b) non-linearly quantizing the Lx5 number of normalized edge histogram bins to generate Lx5 number of quantization index values for the target image; c) storing the Lx5 number of quantization index values to the database; and d) repeating the steps a) to c) until all of the stored images are processed to thereby construct the database having the image information.
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Description

technical field

[0001] The present invention relates to a method for retrieving image data, in particular to a method for constructing a bit representation of an edge histogram descriptor with reduced bits and a method for using a coding expression derived from said descriptor A method for retrieving image data by efficiently extracting information from it. Background technique

[0002] Joint Photographic Experts Group (JPEG) is an international standard for still images, and Moving Picture Experts Group-1 (MPEG-1), 2 is a standard for moving images. Regarding compressed image information, feature information of each image can be extracted for applications such as extraction of key frames, image search, browsing, and the like.

[0003] To extract feature information, brightness or color histograms are widely used. The brightness and color histograms represent the relative frequency of brightness and color (red, green or blue), respectively, in an image. In particular, var...

Claims

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