Feature Points Extraction of Chinese Characters Based on Blob Algorithm

Abstract:

The feature points extraction plays an essential role in modeling structure of Chinese characters for accurate recognition. The distortions caused by the thinning process make the thinning-based stroke segmentation difficult for extracting feature points and handle the ambiguous intersection regions. This paper proposes a novel method that overcomes the distortions to extract feature points from the thinned Chinese characters. Firstly, we use eight structural elements to thin a Chinese character in a series combined way, and then segment different kinds of strokes according to their properties after thinning preprocessing. Finally we draw the end points of every stroke based on the Blob algorithm and obtain the cross information at the same time. The feature points will be abstracted fast and exactly. The experimental results show that the proposed method is effective for Chinese characters recognition (CCR).

• Periodical: Advanced Materials Research (Volumes 433-440)
• Pages: 4214-4219
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.433-440.4214
• Online since: January 2012
• Authors: Xiao Yin Huang, Ning Fang
• Keywords: Blob Algorithm, CCR, Feature Points Extraction

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