An efficient ant-based edge detector is presented. It is based on the distribution of ants on an image, ants try to find possible edges by using a state transition function based on 5x5 edge structures. Visual comparisons show that the proposed method gives finer details and thinner edges at lesser computational times when compared to earlier ant-based approaches. When compared to standard edge detectors, it shows robustness to Gaussian and Salt & Pepper noise and provides finer details than others with same parameter set in both clear and noisy images. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
AydIn, D. (2010). An efficient ant-based edge detector. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6220 LNCS, pp. 39–55). https://doi.org/10.1007/978-3-642-15034-0_3
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