Multi-threading based implementation of ant-colony optimization algorithm for image edge detection
Beg, M.M. Sufyan
MetadataShow full item record
This item's downloads: 533 (view details)
Cited 2 times in Scopus (view citations)
Aslam, Asra and Khan, Ekram and Beg, MM Sufyan (2015) Multi-threading based implementation of Ant-Colony Optimization algorithm for image edge detection," 2015 Annual IEEE India Conference (INDICON), New Delhi, 2015, pp. 1-6. doi: 10.1109/INDICON.2015.7443603
Ant Colony Optimization (ACO) is a nature inspired algorithm for solving optimization problems and is proved to be a powerfnl tool in image processing. It works on the principle that an ant while moving leaves pheromones on its path, which is used as guide to be followed by other ants. ACO is complex and time consuming. In this paper, a multi-threading based implementation of ACO is proposed for identifying edges in images. It combines multi-threading with ACO for increasing the randomness among the artificial ants. The algorithm is implemented and its performance is measured in terms of time complexity. Simulation results show that the proposed method has significantly lower execution time as compared to conventional ACO for edge detection.