Character identification technique based on Gabor filter set

A filter bank and character recognition technology, applied in the field of character recognition, can solve problems such as poor recognition performance, inability to extract stroke direction, structural information, and poor ability to distinguish character details.
CN1459761AInactive Publication Date: 2003-12-03TSINGHUA UNIV
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
TSINGHUA UNIV
Publication Date
2003-12-03
Estimated Expiration
Not applicable Β· inactive patent

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Abstract

A character recognizing technology based on Gabor filter group includes using Gabor filter group to extract the strokes of a character image in different directions, finding out optimal filter parameters, non-linear post-processing to the output of Gabor filter group for increasing the resistance of recognizing system to brightness, contrast change and interference of image, calculating the recognizing characteristics of the positive and negative values in said output, combining them, together to obtain a multi-dimension characteristic vector, and reducing its number of dimensions by linear analysis method to improve its recognizing performance. Its advantage is high recognition percentage.
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Description

technical field

[0001] The character recognition method based on the Gabor filter bank belongs to the field of character recognition (referred to as OCR). Background technique

[0002] The traditional character recognition technology is based on the character image after binarization, so when it is applied to various low-quality images, such as low-resolution images, ID card images, car license plates, and natural scene images, due to the binary The character image quality after valueization is low, and the recognition performance is poor. Therefore, many techniques directly extract recognition features from grayscale character images. Generally, terrain features, gradient edge features, etc. are extracted by analyzing the gradient distribution of the gray image. These methods require the image brightness distribution to meet some specific rules, and the anti-interference ability is very poor; or use simple orthogonal transformation methods such as FFT and DCT. These trans...

Claims

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