Abstract
This paper presents a novel optimal edge detection scheme based on the concepts of fuzzy Smallest Univalue Assimilating Nucleus (SUSAN) and JADE (an adaptive Differential Evolution variant with Optional External Archive). Initially, the Univalue Assimilating Nucleus (USAN) area is calculated from the intensities of every neighborhood pixel of a pixel of interest in the test image. The USAN area edge map of each of the RGB components is fuzzified subject to the optimization of fuzzy entropy, together with fuzzy edge sharpness factor, using JADE. Adaptive thresholding converts the fuzzy edge map to spatial domain edge map. Finally, the individual RGB edge maps are concatenated to obtain the final image edge map. Qualitative and quantitative comparisons have been rendered with respect to a few promising edge detectors and also optimal fuzzy edge detectors based on metaheuristic algorithms like the classic Differential Evolution (the classic DE/rand/1) and the Particle Swarm Optimization (PSO).KeywordsParticle Swarm OptimizationEdge DetectorFuzzy EntropyAdaptive ThresholdingUSAN AreaThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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