An Adaptive Differential Evolution Based Fuzzy Approach for Edge Detection in Color and Grayscale Images

• Published in: Swarm, Evolutionary, and Memetic Computing Vol. 8297; pp. 260 - 273
• Main Authors: Mukherjee, Satrajit, Majumder, Bodhisattwa Prasad, Piplai, Aritran, Das, Swagatam
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2013; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Adaptive Thresholding; Edge Detector; Fuzzy Entropy; Particle Swarm Optimization; USAN Area
• ISBN: 3319037528; 9783319037523
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-03753-0_24

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).