A method and system for end-to-end indefinite-length character recognition

Abstract

The invention discloses an end-to-end indefinite-length character recognition method and system, which is characterized in that: according to pictures and text character tags in a data set, a text detection model and a text recognition model are trained by using a depth neural network; Through the text detection model, the position of the text in the picture is located. Identify the specific content of the text through the text recognition model; The two models are combined to recognize the characters in the picture and locate the positions of the characters in the picture, so that the characters in the picture can be recognized and the positions of the characters in the picture can be known, which can be applied to the directions of the traditional character recognition and the certificate recognition, and the efficiency and accuracy of the character input can be greatly improved.

Description

technical field [0001] The invention relates to the field of image recognition, in particular to an end-to-end variable-length text recognition method and system. Background technique [0002] The concept of optical text recognition was first proposed by German scientist Tausheck in 1929, and later American scientist Handel also proposed the idea of ​​using technology to recognize text. Casey and Nagy of IBM Corporation were the first to study the recognition of printed Chinese characters. In 1966, they published the first article on Chinese character recognition, using the template matching method to recognize 1000 printed Chinese characters. [0003] As early as the 1960s and 1970s, countries around the world began to conduct research on OCR (Optical Character Recognition, Optical Character Recognition). In the early stages of research, most of the research was on text recognition methods, and the recognized text was only 0 to 9. number. Take Japan, which also has square...

AI Technical Summary

Problems solved by technology

China's research work on OCR technology started relatively late. It was only in the 1970s that the research on the recognition of numbers, English letters and symbols began. In the late 1970s, the research on Chinese character recognition began. In the early stage, many research units launched Chinese OCR products one after another. The early OCR software failed to meet the actual requirements due to various factors such as recognition rate and productization.

At the same time, due to the high cost of hardware equipment and slow running speed, it has not reached a practical level.

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