Chinese text recognition method in natural scene images based on two-dimensional recurrent network

Abstract

The present invention discloses a Chinese text recognition method in the natural scene image based on the two -dimensional recursive network. The first training sample set is obtained.Training the neural network connected to the connection; in the depth convolution network after training the test sample input training, get the feature diagram of the test sample; then enter the feature diagram of the test sample intoTest the coding feature diagram of the test sample; then enter the decoding of the coding feature diagram of the test sample in the two -dimensional recursive network to obtain the probability result of each commonly used Chinese character in each frame image of the test sample;The overall Chinese text in the test sample.The method of this invention makes full use of the spatial time information of text images and the context information, which can avoid the problem of pre -segmentation of text images and improve the accuracy of identification.

Description

technical field [0001] The invention belongs to the field of image text analysis and recognition, in particular to a method for recognizing Chinese text in natural scene images based on a two-dimensional recursive network. Background technique [0002] Most of the human information is obtained through the visual system. The scene image obtained through the visual system not only contains rich visual information such as color, pattern, shape, position, texture, but also rich text information. The description of information by text has the characteristics of accuracy and validity, and text has very useful value in various computer vision applications. For example, in terms of image search, recognizing the text in the image will help us better classify and match the image; in terms of unmanned driving, recognizing the text information of traffic signs and other signs from natural scenes can assist driving. In today's rapid development of artificial intelligence, text recogniti...

AI Technical Summary

Problems solved by technology

However, this kind of method still has certain defects. For example, the distortion of the text in the image, such as rotation and transmission, requires a large number of sample training to enhance the recognition ability of the network. When recognizing a one-dimensional recursive network, it is necessary to first convert the two-dimensional feature map into a one-dimensional image. dimensional feature sequence

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