Chinese Character Recognition in Complex Images Based on  #br# Improved SURF Descriptor Features and Fuzzy Reasoning

doi:10.3969/j.issn.1006-2475.2019.04.013

Abstract

Abstract: In considering the robustness of Chinese characters matching to the variations of orientation, position and brightness, this paper describes a new method based on improved Speeded Up Robust Features named SSURF to extract characters features. Firstly, the SSURF descriptors of the same class samples are matched. Then the matching rate of key points whose matching times exceed 1/2 is calculated. Finally, the mean value of SSURF descriptors of training samples and the maximum Euclidean distance between SSURF descriptors and mean values are used to establish class database.Experimental results demonstrate that the proposed method yields a better performance.

Key words: Chinese character recognition, SURF, shape information, fuzzy reasoning, SSURF

CLC Number:

TP391.4

TAO Xiao-jiao, LU Jin . Chinese Character Recognition in Complex Images Based on #br# Improved SURF Descriptor Features and Fuzzy Reasoning[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2019.04.013.

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Chinese Character Recognition in Complex Images Based on #br# Improved SURF Descriptor Features and Fuzzy Reasoning

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