Image processing method and system for OCR image recognition

Abstract

The invention discloses an image processing method for OCR image recognition. The method comprises the following steps: S1, carrying out the preprocessing of a to-be-recognized image, so as to outputimage data meeting a preset specification; S2, reprocessing the preprocessed image to determine the position of the image and perform character positioning on the image; and S3, performing character recognition and correction, and performing feedback type repeated recognition in the character recognition and correction process to obtain a final OCR recognition result. The method and the system aremainly used for identifying machine invoices, various forms and documents; the method is high in recognition precision, high in recognition speed and high in adaptability, the anti-interference capacity in the OCR is enhanced through image preprocessing correction and character positioning, the accuracy of the OCR can be improved through a feedback algorithm (namely a feedback model) based on thecomprehension degree, and the method has high correction capacity for partial information loss and recognition errors. Compared with the recognition effect of the traditional OCR recognition technology, the recognition accuracy is greatly improved.

Description

technical field [0001] The present invention relates to the technical field of Chinese character recognition, specifically, an OCR image recognition method and system. Background technique [0002] OCR (Optical Character Recognition, Optical Character Recognition) technology is to convert the text of various bills, newspapers, books, manuscripts and other printed materials into image information through optical input methods such as scanning, and then use text recognition technology to convert the image information into usable computer input technology. [0003] With the continuous development of image sensors, especially the exponential increase in the number of various mobile phones and professional (such as security) cameras, computer image data is increasing rapidly; but the image quality is relatively lower than that of traditional scanners or various professional cameras; traditional Chinese character OCR technology faces the problem that the quality of the source ima...

AI Technical Summary

Problems solved by technology

According to relevant market surveys in 2018, many traditional OCR manufacturers in the market did not perform well in the testing of various bills photographed by mobile phones. The field has achieved good results, but due to the large base of Chinese characters, the required training data set is thousands of times more than that of Western character sets (conservative estimates), so the performance of Chinese character OCR on the open AI platform is quite poor on poor images. Ideal, and end-to-end deep neural networks have natural misidentifications and are vulnerable to attacks

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