Abstract
For the structural characteristics of Chinese NvShu character, by combining the basic idea in LLT local threshold algorithm and introducing the maximal between-class variance algorithm into local windows, an improved character segmentation algorithm based on local adaptive thresholding technique for Chinese NvShu documents was presented in this paper. Because of designing the corresponding correction parameters for the threshold and using secondary search mechanism, our proposed method could not only automatically obtain local threshold, but also avoid the loss of the character image information and improve the accuracy of the character image segmentation. Experimental results demonstrated its capability to reduce the effect of background noise, especially for Chinese NvShu character images with uneven illumination and low contrast
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