Title :
The skeletonization research of low-quality Chinese characters based on principal curves
Author :
Yang, Mian ; Liao, Zhi-wu
Author_Institution :
Sch. of Comput. Sci., Sichuan Normal Univ., Chengdu, China
Abstract :
The skeleton which keeps the topology information as well as reduces the computational complexity is an excellent and robust structural feature to noise and deformation. This paper focuses on the skeletonization of low-quality free handwritten or printed Chinese characters with fuzziness, deformation, sparseness and discontinuity. We use a simple scheme to optimize the initial Hamilton path obtained from the soft K-segments algorithm and then propose a scheme based on the overall average sparseness to set the threshold, thus to delete the redundant edges. Experimental results show that skeletons obtained from this proposed scheme closely conform to human perception without any artifact.
Keywords :
computational complexity; curve fitting; deformation; fuzzy set theory; graph theory; handwritten character recognition; optimisation; computational complexity; deformation; handwritten character; initial Hamilton path optimization; low-quality Chinese character skeletonization; principal curve; redundant edge; soft K-segments algorithm; Clouds; Computational complexity; Cybernetics; Humans; Iterative algorithms; Machine learning; Noise robustness; Shape; Skeleton; Topology; Chinese character; Hamilton path; average sparseness; low-quality; principal curves; skeleton;
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
DOI :
10.1109/ICMLC.2009.5212775