Kanji Recognition in Scene Images using Distortion Parameter Estimation based on Support Vector Regression

S. Ando, Y. Kusachi, A. Suzuki, K. Arakawa, and T. Yasuno (Japan)


Kanji recognition in scene images, Parameter estimation, Principle component analysis, Support vector regression


Kanji character recognition in scene images is being actively researched for the purpose of indexing in image retrieval. Character recognition in scene images is the technique of detecting and recognizing characters from general images taken with a digital camera. It needs high performance since most characters lie on backgrounds that have complicated textures and are geometrically distorted because of view angles. In this paper, we propose a novel method that starts by estimating the geometric distortion of the characters through support vector regression and then recognizes the character minus the distortion. Experiments show that the proposed method has higher recognition rate due to the distortion correction.

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