TY - GEN
T1 - Chaotic mutated bat algorithm optimized edge potential function for target matching
AU - Deng, Yimin
AU - Duan, Haibin
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/11/20
Y1 - 2015/11/20
N2 - In this paper, we present a novel edge based matching approach to target recognition. To recognize the marker on a rotorcraft, a chaotic mutated bat algorithm optimized edge potential function approach is proposed to accomplish the matching between the sketch image and the scene in real applications. A novel type of attractive contour pattern is acquired using the edge potential function. These edge structures can be conveniently exploited for target matching. Bat algorithm is adopted for the optimization problem of searching the optimal match in the scene, and a chaotic mutated bat algorithm is proposed using the chaotic theory and a mutated operator. Thus, the target matching task is converted to optimizing the average of potential value by the processing of translating, reorienting and scaling the sketch image. Series of experiments are conducted to show that our method is superior to other methods. Our proposed method can achieve the higher fitness value over the standard optimization algorithms.
AB - In this paper, we present a novel edge based matching approach to target recognition. To recognize the marker on a rotorcraft, a chaotic mutated bat algorithm optimized edge potential function approach is proposed to accomplish the matching between the sketch image and the scene in real applications. A novel type of attractive contour pattern is acquired using the edge potential function. These edge structures can be conveniently exploited for target matching. Bat algorithm is adopted for the optimization problem of searching the optimal match in the scene, and a chaotic mutated bat algorithm is proposed using the chaotic theory and a mutated operator. Thus, the target matching task is converted to optimizing the average of potential value by the processing of translating, reorienting and scaling the sketch image. Series of experiments are conducted to show that our method is superior to other methods. Our proposed method can achieve the higher fitness value over the standard optimization algorithms.
KW - bat algorithm
KW - chaotic mutated operator
KW - edge potential function
KW - target matching
UR - https://www.scopus.com/pages/publications/84960850425
U2 - 10.1109/ICIEA.2015.7334262
DO - 10.1109/ICIEA.2015.7334262
M3 - 会议稿件
AN - SCOPUS:84960850425
T3 - Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015
SP - 1049
EP - 1053
BT - Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015
Y2 - 15 June 2015 through 17 June 2015
ER -