Dr. Ming-Te Chao Profile

Dr. Ming-Te Chao

at Yuan Ze Univ

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Proceedings Article | 6 September 2019 Paper

A compact representation of character skeleton using skeletal line based shape descriptor

Ming-Te Chao, Yung-Sheng Chen

Proceedings Volume 11137, 111372P (2019) https://doi.org/10.1117/12.2529933

KEYWORDS: Shape analysis, Image processing, Reconstruction algorithms

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Skeletonization is a quite significant technology for the shape representation in the field of image processing and pattern recognition. In order to explore its application onto the Chinese calligraphy character representation and reconstruction, a skeletal line based shape descriptor has been presented by the authors recently. Its performances evaluated by measurement of skeleton deviation (MSD), number of distorted forks (NDF), number of spurious strokes (NSS) as well as measurement of reconstructability (MR) showed that the skeleton-biased phenomenon can be greatly reduced and the pattern reconstructability near to 100% can be achieved. However, due to the use of dense skeletal line (SL) placement scheme, a lot of memory space is needed for storing the extended and dense SL information; and the computation cost is also rather expensive. Therefore, a compact strategy is presented in this paper to overcome these issues. Instead of storing all the SL information, only the sampled SL with a certain interval will be stored in the skeleton table. By performing the curve-fitting strategy derived from Vandermonde matrix onto the sampled SL information in the skeleton table, both the required skeleton and pattern contour can be readily restored, and the original pattern can thus be reconstructed. The sampling interval (SI) from 1 to 6 are used in our experiments (with 15 Chinese calligraphy characters) and the original method is regarded as the ground truth. Our experimental results show that the memory space can be approximately reduced from 54% (SI = 1) to 92% (SI = 6). The pattern reconstructability can still be maintained from 95% (SI = 1) to 92% (SI = 6). Moreover, the mean execution time of pattern reconstruction can be greatly reduced from 7.814 sec (the original method) to 0.078 sec (the improved method). The results confirm the feasibility of the proposed approach.

SPIE Journal Paper | 22 January 2018

Skeletonization application: Chinese calligraphy character representation and reconstruction

Yung-Sheng Chen, Ming-Te Chao

JEI, Vol. 27, Issue 05, 051202, (January 2018) https://doi.org/10.1117/12.10.1117/1.JEI.27.5.051202

KEYWORDS: Reconstruction algorithms, Chaos, Shape analysis, Neck, Image segmentation, Algorithm development, Laser sintering, Visualization, Binary data, 3D image reconstruction

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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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