Multilevel image thresholding based on tsallis entropy and differential evolution

Authors:
Soham Sarkar;Swagatam Das;Sheli Sinha Chaudhuri
Affiliations:
Electronics and Communication Engineering Department, RCC Institute of Information Technology, Kolkata, India;Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India;Electronics and Telecommunication Engineering Department, Jadavpur University, Kolkata, India
Venue:
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
Year:
2012

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Abstract

Image segmentation is known as one of the most critical task in image processing and pattern recognition in contemporary time, for this purpose Multi Level Thresholding based approach has been an acclaimed way out. Endeavor of this paper is to focus on obtaining the optimal threshold points by using Tsallis Entropy. In this paper, we have incorporated a Differential Evolution (DE) based technique to acquire optimal threshold values. Furthermore, results are compared with two state-of-art algorithms- a. Particle Swarm Optimization (PSO), and b. Genetic Algorithm (GA). Several image quality assessment indices are applied for the performance analysis of the outcome derived by applying the proposed algorithm.