Character recognition system and method based on the combination of neural network and attention mechanism

Abstract

The present invention claims to protect a character recognition system and method based on the combination of neural network and attention mechanism, which specifically includes: a convolutional neural network feature extraction module for spatial features of text images; inputting the spatial features extracted by the convolutional neural network To the two-way long-short-term memory network module, the two-way long-short-term memory network can extract the sequence features of the text; the extracted feature vectors are semantically encoded, and then the attention weights of the feature vectors are assigned through the attention mechanism, so that attention can be focused on the weights Higher feature vector; the decoding part of the model is realized by nesting long-term short-term memory network, and the features extracted by attention and the prediction information at the previous moment are used as the input of nested long-term short-term memory network, and long-term short-term memory is used before and after The purpose of the network is to maintain the time characteristics of the feature vector, so that the model pays attention to the continuous change of the position point with time; the invention can more accurately detect the text area in the natural scene, and has a good effect on the small target text and the text with a small inclination angle. Good detection effect.

Description

technical field [0001] The invention belongs to character and image recognition in natural scenes, and relates to a correlation algorithm combining a convolutional neural network, a long-term short-term memory network and an attention mechanism. Background technique [0002] Natural scenes are the living environment we live in. Natural scene images contain a variety of visual information, such as text, cars, landscapes, organisms, and architectural landscapes. These elemental information constitute the main content of natural scenes. Element. [0003] Digital recognition in natural scenes belongs to the category of text recognition in natural scenes. The research on text recognition in natural scenes began in the 1990s, but it is still an unsolved problem until now. Generally speaking, the text recognition task in natural scenes consists of two parts: text region detection and text recognition. Text recognition is based on detection, and the detected text box is used as re...

AI Technical Summary

Problems solved by technology

However, due to many factors such as the position, deformation, and illumination of the characters in the natural scene, and the background of the characters in the natural scene is also quite complicated, there are many technical difficulties that need to be overcome in the recognition

[0004] At present, many research methods are mostly based on top-down algorithm models. Jaderberg et al. designed an end-to-end recognition method based on convolutional neural network and structured output, but the length of the text needs to be fixed. The text recognition effect is not good. Shi et al. proposed an end-to-end recognition method based on "convolutional neural network + cyclic neural network + sequence classification", but this method is not effective for complex text image recognition.

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