Abstract
Digital image processing is a research topic that has been studied from different perspectives. In this paper we propose an approach based on a paradigm that arises from artificial life; more specifically ant colonies foraging behavior. Ant based algorithms have shown interesting results in a wide variety of situations, including optimization and clustering. In this work we compare different ant colony algorithms on a set of images, for the detection of edges. Results are presented as images, in which ants have built specific solutions, and discussed within an image-processing framework. © 2013 Springer-Verlag.
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CITATION STYLE
Contreras, R., Pinninghoff, M. A., & Ortega, J. (2013). Using ant colony optimization for edge detection in gray scale images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7930 LNCS, pp. 323–331). https://doi.org/10.1007/978-3-642-38637-4_33
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