Baseline Image Classification Approach Using Local Minima Selection
IVIC '09 Proceedings of the 1st International Visual Informatics Conference on Visual Informatics: Bridging Research and Practice
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Handwritten words are usually slant or Italicized due to the mechanism of handwriting and the personality. In order to improve the accuracy of character segmentation and recognition, the authors proposed a chain code method for the slant estimation and correction. However the method is very simple and usually gives good estimate of the word slant, there was a problem such that the slant tends to be underestimated when the absolute of the slant is close or greater than 45 degree. To solve the problem, we proposed an iterative chain code method. In this paper, we introduce a new non-iterative method using 8-directional chain code for improving the linearity and the accuracy of the slant estimation. The experimental results show that the proposed method improves the linearity and the accuracy of the slant estimation efficiently without sacrificing the processing speed and the simplicity.