Burmese Image Text Recognition Method Based on CRNN

A text recognition and image technology, applied in character recognition, neural learning methods, character and pattern recognition, etc., can solve the problem of difficult extraction of text information in Burmese images, achieve good results, high recognition accuracy, and solve difficult extraction problems Effect

Active Publication Date: 2021-03-02
小语智能信息科技(云南)有限公司
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AI Technical Summary

Problems solved by technology

[0003] The invention provides a Burmese image text recognition method based on CRNN, which is used to identify and extract Burmese text information on the image, and solves the problem that the text information in the Burmese image is difficult to extract

Method used

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  • Burmese Image Text Recognition Method Based on CRNN
  • Burmese Image Text Recognition Method Based on CRNN
  • Burmese Image Text Recognition Method Based on CRNN

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Embodiment 1

[0059] Embodiment 1: as Figure 1-2 Shown, based on the Burmese image text recognition method of CRNN, the concrete steps of described method are as follows:

[0060] Step1. Data preprocessing: Combining Burmese language features to construct training sets, test sets, and evaluation set data of long sequences and short sequences of Burmese text information images of different dynamic segments; for example, long sequence data short sequence data

[0061] Then use the Burmese Unicode sorting algorithm to mark the text information in the Burmese image. Before the training task starts, all the input Burmese image pixels are scaled to a fixed 120*32 resolution for the next deep convolutional neural network input;

[0062] Step2, feature vector sequence extraction: use the deep convolutional neural network (CNN) to extract the corresponding feature vector sequence from the input Burmese image, and use the convolutional layer and the maximum pooling layer in the deep convolutiona...

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Abstract

The invention relates to a Burmese image text recognition method based on CRNN, and belongs to the field of natural language processing. The invention includes the steps of: constructing training set, test set and evaluation set data of Burmese text information images; using Burmese Unicode sorting algorithm to mark the text information in Burmese images; Extract the corresponding feature vector sequence; use BiLSTM in the cyclic neural network RNN ​​to identify the feature vector sequence obtained in the previous step, obtain the context information of the sequence, and obtain the probability distribution of each column feature; use CTC to calculate the probability of all label sequences, Based on the dictionary and the pattern of finding candidate targets, the tag sequence corresponding to the maximum tag sequence probability is selected as the final prediction result of Burmese for each frame in the image. The invention realizes the recognition of Burmese image text, and has high recognition accuracy and good effect.

Description

technical field [0001] The invention relates to a Burmese image text recognition method based on CRNN, and belongs to the technical field of natural language processing. Background technique [0002] Burmese image text recognition is a basic task in Burmese natural language research. Burmese text information on traditional images cannot be directly recognized and extracted by computer, and the text on images cannot be used for natural language processing research. The usual processing method They are all manually typed out by looking at the pictures, which is time-consuming and labor-intensive. At present, the method of combining deep learning in Chinese and English image text recognition tasks has achieved very good results, but there has been no breakthrough in the field of Burmese image text recognition. Because of the special syllable structure of Burmese, one syllable It may be composed of multiple characters and cannot be separated. Unlike English or Chinese, only a s...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/049G06N3/08G06V30/10G06N3/045G06F18/214G06F18/2415
Inventor 毛存礼谢旭阳余正涛高盛祥
Owner 小语智能信息科技(云南)有限公司
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