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Method for extracting characteristic of handwritten Chinese character image

A feature extraction, Chinese character technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve the problem that the positioning cannot extract scale-invariant features, and achieve the effect of improving the recognition performance

Inactive Publication Date: 2009-06-03
SOUTH CHINA UNIV OF TECH
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Problems solved by technology

[0008] The purpose of the present invention is to overcome the problem that the direct application of SIFT feature point positioning cannot extract effective scale-invariant features suitable for different writing styles, combining the characteristics of handwritten Chinese character images, using elastic grid technology and SIFT statistical area gradient information to describe the area Based on the principle of elastic region gradient information, a handwritten Chinese character feature extraction method is designed based on the dynamic statistical histogram

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  • Method for extracting characteristic of handwritten Chinese character image
  • Method for extracting characteristic of handwritten Chinese character image

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Embodiment Construction

[0032] The flow chart of the dynamic gradient statistical feature extraction method of the present invention is as attached image 3 As shown, specifically, on the one hand, the input Chinese character image is divided into elastic grids to obtain 64 sub-regions, and then the center point of the sub-region is determined as the seed point, and a gradient statistical vector is assigned to each seed point. On the other hand, Obtain the gradient direction vector of each pixel in the image, obtain the gradient information of each pixel by decomposing the gradient vector, and then weight and accumulate the gradient information of each pixel point to the seed point of the adjacent sub-region according to the rules, and then put Each statistical vector is normalized, and finally the statistical vectors are sequentially spliced ​​into the final feature vector output.

[0033] The schematic diagram of the adjacent sub-region mentioned in step (3) of the feature extraction method of the ...

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Abstract

The invention provides a method for extracting characteristic of a handwritten Chinese character image. The global handwritten Chinese character image is used as a characteristic extraction area; furthermore, a Chinese character image area is divided by an elastic network; scale invariability characteristic conversion method is employed to carry out dynamic statistics of gradient direction information of relative areas on each network, thus gaining the characteristic of a handwritten Chinese character. The method randomly selects 500 samples from a HCL2000 handwritten Chinese character sample database to carry out a training and selects 200 non-repeated samples to carry out a recognition test; the recognition result when the method is used for gaining characteristic is that the hit ratio of a firstly selected character is 96.061% and the hit ratio of the first 10 candidate characters is 99.688%.

Description

technical field [0001] The invention belongs to the technical field of pattern recognition and artificial intelligence, in particular to a handwritten Chinese character image recognition processing method. technical background [0002] A handwritten Chinese character recognition system is divided into four modules: preprocessing, feature extraction, classification recognition, and postprocessing. Feature extraction is considered to be one of the key steps in Chinese character recognition and has an important impact on the final performance of the entire system. In recent years, many scholars have done a lot of research work on how to obtain effective features, and achieved many excellent results. The Gabor feature is one of the more effective features of various Chinese characters, and its application has a good biological vision theory support behind it. In fact, pattern recognition has always been closely related to computer vision and biological vision theory. [0003] ...

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Application Information

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IPC IPC(8): G06K9/00G06K9/46G06K9/62
Inventor 金连文张志毅丁凯
Owner SOUTH CHINA UNIV OF TECH
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