Optimization in edge detection using ant colony optimization

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Abstract

Image processing is now emerged in different fields like medical, security and surveillance, remote sensing & satellite applications and much more. Image processing includes different operations such as feature extraction, object detection and recognition, X-ray scanning etc. All such operations required edge detection to get better quality image. Edge detection is performed to distinguish different objects in an image by finding the boundaries or edges between them. Edges are used to isolate particular objects from their background as well as to recognize or classify objects. In this paper, comparison of various edge detection techniques such as Sobel, Prewitt, Roberts, Canny, LoG and Ant Colony Optimization Algorithm is given. Ant colony Optimization(ACO) use parallelism which reduces the computation time as size of an image increases.

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Kasare, P., Kulkarni, J., & Bichkar, R. (2019). Optimization in edge detection using ant colony optimization. International Journal of Recent Technology and Engineering, 8(3), 8167–8170. https://doi.org/10.35940/ijrte.C6134.098319

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