Handwritten Armenian Character Recognition Based On Discrete Cosine Transform and Artificial Immune System
Artificial Immune System1 is engineering system which has been inspired from the functioning of the biological immune system. In this paper, handwritten Armenian character recognition strategy using artificial immune system was proposed and carefully experimented. With 90 feature coefficients extracted from 24*24 Armenian character image using DCT based on 8*8 image sub-block as its feature vector, 38 antibody libraries for 38 character category were trained and built to recognize Armenian characters with artificial immune algorithm. The contrast experiment was done using three-tiered feed-forward, back-propagation neural network model with sigmoid transfer function, 0.01 learning rate parameter and the same input feature coeffkients8. The experimental results indicated that the artificial immune system model has more advantages than BP neural network in character recognition.
DCT sub-meshing artificial immune system
YUYANG
Basic Department The Chinese Peoples Armed Police Forces Academy, Langfang, China
国际会议
重庆
英文
517-519
2011-08-20（万方平台首次上网日期，不代表论文的发表时间）