Adaptive edge detection using adjusted ant colony optimization

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Abstract

Edges contain important information in image and edge detection can be considered a low level process in image processing. Among different methods developed for this purpose traditional methods are simple and rather efficient. In Swarm Intelligent methods developed in last decade, ACO is more capable in this process. This paper uses traditional edge detection operators such as Sobel and Canny as input to ACO and turns overall process adaptive to application. Magnitude matrix or edge image can be used for initial pheromone and ant distribution. Image size reduction is proposed as an efficient smoothing method. A few parameters such as area and diameter of travelled path by ants are converted into rules in pheromone update process. All rules are normalized and final value is acquired by averaging.

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APA

Davoodianidaliki, M., Abedini, A., & Shankayi, M. (2013). Adaptive edge detection using adjusted ant colony optimization. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives (Vol. 40, pp. 123–126). International Society for Photogrammetry and Remote Sensing. https://doi.org/10.5194/isprsarchives-xl-1-w3-123-2013

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