Handwritten Icelandic Character Recognition Based On Artificial Immune System
Artificial immune systems1-2 are highly distributed systems based on the principles of the natural system. In this paper, handwritten Icelandic character recognition strategy using artificial immune system was proposed and carefully experimented. With 73 feature coefficients extracted from 24*24 handwritten Russian uppercase character image using 36 sub-meshing coefficients, 24 traversing-times coefficients, 1 segmentation-times coefficients and 12 .vertical projection coefficients as its feature vector, 32 antibody libraries for 32 character category were trained and built to recognize handwritten Icelandic 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 Icelandic uppercase character recognition。
traversing-times coefficients 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
520-523
2011-08-20（万方平台首次上网日期，不代表论文的发表时间）