Title :
Handwritten Character Recognition Based on 13-point Feature of Skeleton and Self-Organizing Competition Network
Author :
Zhong, Chongliang ; Ding, Yalin ; Fu, Jinbao
Author_Institution :
Changchun Inst. of Opt., Fine Mech. & Phys., Chinese Acad. of Sci., Changchun, China
Abstract :
This article is about the recognition for handwritten characters. Firstly, we use some conventional methods to preprocess the images and introduce the 13-point feature of skeleton method to extract the data that containing feature of the handwritten character. Secondly, we use the data to train the self-organizing competition network. In the end, we test the net and conclude that this method has a good performance at handwritten character recognition.
Keywords :
feature extraction; handwritten character recognition; self-organising feature maps; data extraction; handwritten character recognition; self-organizing competition network; skeleton feature; Artificial neural networks; Character recognition; Feature extraction; Handwriting recognition; Image segmentation; Optical character recognition software; Optical fiber networks; Pattern recognition; Physics; Skeleton; 13-point feature of skeleten; ANN; character recognition; image processing; self-organizing competition network;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
DOI :
10.1109/ICICTA.2010.837
