Title :
Digital image edge detection using an ant colony optimization based on genetic algorithm
Author :
Rahebi, Javad ; Elmi, Zahra ; Nia, Ali Farzam ; Shayan, Kamran
Author_Institution :
Fac. of Electr. Eng., Sadjad Univ. of Mashhad, Mashhad, Iran
Abstract :
In this paper a new method for enhancement of digital image edge detection using ant colony optimization based on genetic algorithm has been used. In the proposed method first by the series of answers has been formed by artificial ants and then formed in a manner i.e. useful for genetic algorithm, then the answers played the role as initial population for genetic algorithm and the next population is made by genetic algorithm. Our method compared with Jing Tian method enjoys higher speed, less processing time and more answer´s optimum. Also the proposed method has a better edge than other classical methods (such as sobel, etc).
Keywords :
edge detection; genetic algorithms; Jing Tian method; ant colony optimization; artificial ants; digital image edge detection; genetic algorithm; Ant colony optimization; Digital images; Fluctuations; Genetic algorithms; Genetic engineering; Image edge detection; Java; Pixel; Ant colony optimization; Edge detection; Genetic Algorithm;
Conference_Titel :
Cybernetics and Intelligent Systems (CIS), 2010 IEEE Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-6499-9
DOI :
10.1109/ICCIS.2010.5518567