An edge detection method based on good point set genetic algorithm

In order to improve the convergence rate of the genetic algorithm based on edge detection, a novel edge detection method based on good point set genetic algorithm(GGA) was proposed. The proposed method first redesigns the crossover operation by using the theory of good point set in which progeny inh...

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Bibliographic Details
Main Authors: Guo Yutang, Liu Lulu
Format: Conference Proceeding
Language:chi ; eng
Subjects:
Artificial neural networks
Convergence
Edge detection
Electronic mail
Entropy
Filtering
Fuzzy entropy
Genetic algorithm
Genetic algorithms
Good set
Image edge detection
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Summary:In order to improve the convergence rate of the genetic algorithm based on edge detection, a novel edge detection method based on good point set genetic algorithm(GGA) was proposed. The proposed method first redesigns the crossover operation by using the theory of good point set in which progeny inherits the common genes of parents which represent its family so as to improve the convergence rate of the genetic algorithm. Furthermore, the proposed method offers another better way to improve the convergence rate, that is, to reduce solution domain by pre-processing image to filtering non edge pixel before the algorithm executing. Experimental results show the proposed algorithm performs very well in terms of convergence rate. The detected edge image is well localized, and thin, and robust to noise.
ISSN:1934-1768
2161-2927
DOI:10.1109/CHICC.2008.4605754