Color Image Segmentation By Cuckoo Search

Abstract

In this paper, a clustering based color image segmentation technique is proposed and the clustering technique is optimized by the cuckoo search method. The proposed approach consists of two phase segmentation processes. In the first phase, cluster centres are optimized by using the cuckoo search algorithm and in the second phase, empty and frequent clutters are removed and merged according to pre-defined rules. This cluster centre based clustering technique is then used to find the optimum centre within a cluster, while cuckoo search is applied to find the optimum cluster centre for each segment in the image. Comparison of the proposed method is performed with the genetic algorithm (GA), dynamic control particle swarm optimization (DCPSO) algorithm and firefly algorithm based color image segmentation methods over five benchmark color images. The parameters of the proposed method are tuned through empirical testing. Results demonstrated that the proposed method can be an effective tool for image segmentation.

Keywords::

• Cuckoo search
• Nature-inspired algorithm
• Genetic algorithm (GA)
• Dynamic control particle swarm optimization (DCPSO)
• Firefly algorithm
• Clustering based image segmentation

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Sudarshan Nandy

Sudarshan Nandy received Ph.D. (Engg.) from University of Kalyani, 2014. He completed his Bachelor and Masters in Computer Science and Engineering from Utkal University, and West Bengal University of Technology in the year of 2004 and 2007 respectively. He has been serving as Assistant Professor in JIS College of Engineering, since 2009. His area of interest is computational intelligence, web intelligence, meta-heuristics & nature-inspired algorithms and neural network.

Xin-she Yang

Xin-She Yang received Ph.D. (Phil) from University of Oxford, and currently he is a Reader in Modelling and Simulation at Middlesex University (UK), IA Engineering Supervisor at Cambridge University (UK). He is an Adjunct Professor at Reykjavik University (Iceland), and Distinguished Professor at Xi'an Polytechnic University (China). He has authored/edited 15 books and published 192 research papers. He is the inventor of firefly algorithm (FA), cuckoo search (CS), bat algorithm (BA), eagle strategy (ES), and flower pollination algorithm (FPA).

Partha Pratim Sarkar

Partha Pratim Sarkar was felicitated with a Ph.D. in Engineering from Jadavpur University in the year 2002. He has obtained his M.E from Jadavpur University in the year 1994. He earned his B.E degree in Electronics and Telecommunication Engineering from Bengal Engineering College (Presently known as Bengal Engineering and Science University,Shibpur) in the year 1991. Currently he is working as Senior Scientific Officer (Professor Rank) at the Dept. of Engineering & Technological Studies, University of Kalyani. He has contributed to numerous research articles in various journals and conferences of repute.

Achintya Das

Achintya Das was born on 8th February 1957. He completed B.Tech., M.Tech and Ph.D. (Tech) in the subject of Radio Physics Electronics from Calcutta University in the years of 1978, 1982 and 1996 respectively. He is Professor and Departmental head of Electronics and Communication Engineering of Kalyani Govt. Engineering College, Kalyani, West Bengal. He also worked for twelve years as Visiting Professor at Calcutta University. He has more than hundred research publications so far.