DocumentCode :
2437995
Title :
A method for the segmentation of connected handwritten Persian digits
Author :
Ashtiany, Fattaneh Taheri ; Faez, Karim
Author_Institution :
Electr. & Comput. Fac., Islamic Azad Univ. of Bonab, Tabriz, Iran
fYear :
2010
fDate :
7-10 Dec. 2010
Firstpage :
1881
Lastpage :
1885
Abstract :
This article presents in two modules a new method for segmenting connected handwritten Persian digits using the characteristics of the foreground and utilizing the background skeleton. The first module excavates all the valleys and hills, if there are any, from the upper pixels and lower pixels of the thinned image respectively. Then feature point excavate. For better segmentation the digits, a separability degree is calculated, regarding the height of the hills and valleys close to each feature point considering the characteristic of connected Persian digits. Then the significance degree is calculated to determine of its influence rate in segmentation. Then, using that, one or few points with high significance degree, which are more influence in the segmentation, are selected as the cutting points. Having excavated the background skeleton, the second module begins to identify the priority points in the skeleton in order to connect them to the cutting points The conducted experiments confirm the accuracy of the factors utilized and the results indicates a correct segmentation at a rate of 97.2%.
Keywords :
feature extraction; handwritten character recognition; image segmentation; optical character recognition; Persian digit segmentation; background skeleton; connected handwritten Persian digits; feature point excavation; separability degree; Character recognition; Feature extraction; Handwriting recognition; Image segmentation; Pixel; Skeleton; Text analysis; Character segmentation; Optical Character Recognition; feature point;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Automation Robotics & Vision (ICARCV), 2010 11th International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-7814-9
Type :
conf
DOI :
10.1109/ICARCV.2010.5707839
Filename :
5707839
Link To Document :
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