Skeletonization application: Chinese calligraphy character representation and reconstruction

Yung-Sheng Chen; Ming-Te Chao

doi:10.1117/1.JEI.27.5.051202

22 January 2018 Skeletonization application: Chinese calligraphy character representation and reconstruction

Yung-Sheng Chen, Ming-Te Chao

Author Affiliations +

Journal of Electronic Imaging, Vol. 27, Issue 5, 051202 (January 2018). https://doi.org/10.1117/1.JEI.27.5.051202

Abstract

Chinese calligraphy is often used to perform the beauty of characters in Chinese culture and is quite suitable in the study of shape representation. The skeleton of a digital line pattern can be treated as the shape descriptor. However, the skeleton-biased and reconstruction-incomplete phenomena often exist in a skeletonization method, which results in the difficulty of using the skeleton to perform the beauty of Chinese calligraphy characters. To overcome this difficulty, skeletal line information derived from the skeletal points and indexed boundary points is defined, and its transformation is implemented by a procedure of two-phase skeletal line placement (SLP). Based on the SLP, an effective algorithm including the SLP-stroke for strokes, SLP-fork for forks, and SLP-end for the end parts of strokes is developed for constructing the skeletal line-based shape descriptor. Four indices of measurement of skeleton deviation, number of distorted forks, number of spurious strokes, and measurement of reconstructability are used to evaluate the performance of the proposed approach. Experimental results show that the skeleton-biased phenomenon can be greatly reduced and the pattern reconstructability close to 100% is achieved, thus confirming that the proposed skeletonization approach is suitable for the Chinese calligraphy character representation and reconstruction.

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Yung-Sheng Chen and Ming-Te Chao "Skeletonization application: Chinese calligraphy character representation and reconstruction," Journal of Electronic Imaging 27(5), 051202 (22 January 2018). https://doi.org/10.1117/1.JEI.27.5.051202

Received: 26 September 2017; Accepted: 7 December 2017; Published: 22 January 2018

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