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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/15653

Title: Dynamic Multilevel Thresholding using Binary Particle Swarm Optimization for Image Segmentation
Authors: Dehimi Houssem
Khelil Naceur
Mohamed Batouche
Issue Date: 2009
Abstract: A new dynamic Multilevel Thresholding method (DMTBPSO), based on Binary Particle Swarm Optimization and Otsu's method, is proposed. This approach can automatically determine the appropriate number of thresholds as well as the adequate threshold values with saving a significant amount of computing time which is independent from the number of thresholds. The proposed method is validated by illustrative examples, comparison with the Otsu's method shows its efficiency.
URI: http://hdl.handle.net/123456789/15653
Appears in Collections:College of Computer and Information Sciences

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