Multi-language scene character recognition method and recognition system

A multi-language and scene technology, applied in the field of text image recognition, can solve problems such as ignoring spatial structure information, unsatisfactory character recognition performance, unsatisfactory dictionary learning and coding strategies, etc.
CN106570521AActive Publication Date: 2017-04-19INST OF AUTOMATION CHINESE ACAD OF SCI
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Patent Information

Authority / Receiving Office
CN Β· China
Current Assignee / Owner
INST OF AUTOMATION CHINESE ACAD OF SCI
Publication Date
2017-04-19

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Abstract

The invention relates to a multi-language scene character recognition method and recognition system. The method comprises the steps that the language type of characters in a scene character image is determined; a deep convolutional neural network model is determined according to the language type of the characters; the convolutional layer characteristics of the scene character image are extracted by using the deep convolutional neural network model; a space pyramid model is established based on the convolutional layer characteristics; high-order coding is performed on each space area on the space pyramid model by using a Gaussian model; the results of high-order coding are spliced to act as scene character descriptors; and the scene character descriptors are classified by using a classifier so as to realize multi-language scene character recognition. The multi-language scene character recognition method and recognition system have great recognition effect on the multi-language scene character image so that the method is a general character recognition method and has great adaptability for multi-language scene character recognition.
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Description

technical field

[0001] The invention relates to the technical field of text image recognition in the field of pattern recognition and machine vision, in particular to a multilingual scene character recognition method and a recognition system. Background technique

[0002] As a symbol designed by humans, text expresses high-level information and is of great help to understanding the content in images. Therefore, the automatic detection and recognition of characters has aroused people's high attention. It has extremely important significance for the storage, classification, understanding and retrieval of images and videos, and has broad application prospects and commercial value.

[0003] However, because the characters in natural scenes are affected by factors such as complex background, uneven illumination, low resolution, various fonts, and different colors, the recognition effect is not satisfactory by directly using traditional optical character recognition (OCR) technolo...

Claims

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