Title :
End-point preserved stroke extraction
Author :
Jian-Jiun Ding ; Pin-Xuan Lee ; Szu-Wei Fu ; Hao-Hsuan Chang ; Chen-Wei Huang
Author_Institution :
Grad. Inst. of Commun. Eng., Nat. Taiwan Univ., Taipei, Taiwan
Abstract :
The stroke is a very important feature for a character and is helpful for word recognition and handwriting identification. Although thinning algorithms can be applied for stroke extraction, they always suffer from the problems of bifurcation and disconnection. Moreover, since the end points of strokes cannot be preserved by thinning, the stroke length cannot be accurately determined and the start and the end parts of a stroke, which are useful for identifying the writing habit of a person, are hard to be extracted explicitly. In this paper, we proposed a very accurate stroke extraction algorithm which can well preserve the ends of strokes. Simulations on some Chinese characters show that the proposed algorithm is reliable and can precisely extract the strokes of characters.
Keywords :
feature extraction; handwritten character recognition; natural language processing; Chinese characters; end-point preserved stroke extraction algorithm; handwriting identification; stroke length; word recognition; Algorithm design and analysis; Bifurcation; Character recognition; Feature extraction; Image edge detection; Noise; Writing; Chinese character identification; feature extraction; forensic image analysis; morphology; stroke extraction;
Conference_Titel :
Audio, Language and Image Processing (ICALIP), 2014 International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4799-3902-2
DOI :
10.1109/ICALIP.2014.7009808