TY - GEN
T1 - An adaptive immune genetic algorithm for edge detection
AU - Li, Ying
AU - Bai, Bendu
AU - Zhang, Yanning
PY - 2007
Y1 - 2007
N2 - An adaptive immune genetic algorithm (AIGA) based on cost minimization technique method for edge detection is proposed. The proposed AIGA recommends the use of adaptive probabilities of crossover, mutation and immune operation, and a geometric annealing schedule in immune operator to realize the twin goals of maintaining diversity in the population and sustaining the fast convergence rate in solving the complex problems such as edge detection. Furthermore, AIGA can effectively exploit some prior knowledge and information of the local edge structure in the edge image to make vaccines, which results in much better local search ability of AIGA than that of the canonical genetic algorithm. Experimental results on gray-scale images show the proposed algorithm perform well in terms of quality of the final edge image, rate of convergence and robustness to noise.
AB - An adaptive immune genetic algorithm (AIGA) based on cost minimization technique method for edge detection is proposed. The proposed AIGA recommends the use of adaptive probabilities of crossover, mutation and immune operation, and a geometric annealing schedule in immune operator to realize the twin goals of maintaining diversity in the population and sustaining the fast convergence rate in solving the complex problems such as edge detection. Furthermore, AIGA can effectively exploit some prior knowledge and information of the local edge structure in the edge image to make vaccines, which results in much better local search ability of AIGA than that of the canonical genetic algorithm. Experimental results on gray-scale images show the proposed algorithm perform well in terms of quality of the final edge image, rate of convergence and robustness to noise.
UR - http://www.scopus.com/inward/record.url?scp=38049073823&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-74205-0_61
DO - 10.1007/978-3-540-74205-0_61
M3 - 会议稿件
AN - SCOPUS:38049073823
SN - 9783540742012
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 565
EP - 571
BT - Advanced Intelligent Computing Theories and Applications
PB - Springer Verlag
T2 - 3rd International Conference on Intelligent Computing, ICIC 2007
Y2 - 21 August 2007 through 24 August 2007
ER -
