DocumentCode
2618917
Title
Application of artificial immune system in handwritten Russian uppercase character recognition
Author
Yang, Yu
Author_Institution
Basic Dept., Chinese People´´s Armed Police Forces Acad., Langfang, China
fYear
2011
fDate
27-29 June 2011
Firstpage
238
Lastpage
241
Abstract
Artificial immune system is computational system inspired by the principles and processes of the vertebrate immune system. It has been applied gradually in many fields upon powerful abilities of information processing and problem solution. In this paper, handwritten Russian uppercase character recognition strategy using artificial immune system was proposed and carefully experimented. With 36 feature coefficients extracted from 36*36 handwritten Russian uppercase character image using 6*6 sub-meshing and 14 contour coefficients as its feature vector, 33 antibody libraries for 33 character category were trained and built to recognize handwritten Russian uppercase characters with artificial immune algorithm. The contrast experiment was done using BP neural network. The experimental results indicated that the artificial immune system model has more advantages than BP neural network in handwritten Russian uppercase character recognition.
Keywords
artificial immune systems; backpropagation; document image processing; edge detection; feature extraction; handwritten character recognition; BP neural network; artificial immune system; computational system; feature extraction; handwritten Russian uppercase character image; handwritten Russian uppercase character recognition; information processing; vertebrate immune system; Artificial neural networks; Character recognition; Cloning; Feature extraction; Handwriting recognition; Immune system; Libraries; artificial immune system; contour coefficients; neural network; sub-meshing;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Service System (CSSS), 2011 International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4244-9762-1
Type
conf
DOI
10.1109/CSSS.2011.5974599
Filename
5974599
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