Edge detection method using unbalanced mutation operator in noise image 


Vol. 9,  No. 5, pp. 673-680, Oct.  2002
10.3745/KIPSTB.2002.9.5.673


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  Abstract

This paper proposes a method for detecting edge using an evolutionary programming and a momentum back-propagation algorithm. The evolutionary programming does not perform crossover operation as to consider reduction of capability of algorithm and calculation cost, but uses selection operator and mutation operator. The momentum back-propagation algorithm uses assistant to weight of learning step when weight is changed at learning step. Because learning rate α is settled as less in last back-propagation algorithm the momentum back-propagation algorithm discard the problem that learning is slow as relative reduction because change rate of weight at each learning step. The method using EP-MBP is batter than GA-BP method in both learning time and detection rate and showed the decreasing learning time and effective edge detection, in consequence.

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[IEEE Style]

S. J. Kim, H. K. Lim, Y. H. Seo, C. Y. Jung, "Edge detection method using unbalanced mutation operator in noise image," The KIPS Transactions:PartB , vol. 9, no. 5, pp. 673-680, 2002. DOI: 10.3745/KIPSTB.2002.9.5.673.

[ACM Style]

Su Jung Kim, Hee Kyoung Lim, Yo Han Seo, and Chai Yeoung Jung. 2002. Edge detection method using unbalanced mutation operator in noise image. The KIPS Transactions:PartB , 9, 5, (2002), 673-680. DOI: 10.3745/KIPSTB.2002.9.5.673.

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