A multilevel color image segmentation technique based on cuckoo search algorithm and energy curve |
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Affiliation: | 1. PDPM Indian Institute of Information Technology Design and Manufacturing, Jabalpur 482005, MP, India;2. Department of Electrical Engineering, Indian Institute of Technology Roorkee, Uttarakhand 247667, India;1. Department of Information Technology, Al-Huson University College, Al-Balqa Applied University, P.O. Box 50, Al-Huson, Irbid, Jordan;2. Department of Computer Science, Al-Aqsa University, P.O. Box 4051, Gaza, Palestine;3. School of Computer Sciences, Universiti Sains Malaysia (USM), Pulau Pinang, Malaysia;4. Department of Computer Science, Faculty of Pure and Applied Sciences, Federal University Wukari, P. M. B. 1029, Wukari, Taraba State, Nigeria;1. Department of EIE, St. Joseph''s College of Engineering, Chennai 600 119, Tamil Nadu, India;2. Institute of Systems and Robotics, University of Coimbra, Ingeniarius, Lda.,Rua da Vacariça, n.37, 3050-381, Mealhada, Portugal |
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Abstract: | Amongst all the multilevel thresholding techniques, standard histogram based thresholding approaches are very impressive for bi-level thresholding. But, it is not effective to select spatial contextual information of the image for choosing optimal thresholds. In this paper, a new color image thresholding technique is presented by using an energy function to generate the energy curve of an image by considering spatial contextual information of the image. The property of this energy curve is very much similar to histogram of the image. To estimate the spatial contextual information for thresholding practice, in place of histogram, the energy curve function is used as an input. A new energy curve based color image segmentation approach using three well known objective functions named Kapur’s entropy, between-class-variance, and Tsalli’s entropy is proposed. In this paper, cuckoo search (CS) and egg lying radius-cuckoo search (ELR-CS) optimization algorithms with different parameter analysis have been used for solving the color image multilevel thresholding problem. The experimental results demonstrate that the proposed CS-Kapur’s energy curve based segmentation can powerfully and accurately search the multilevel thresholds. |
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Keywords: | Image segmentation Multi-level thresholding Energy curve Kapur’s function Tsallis entropy and Otsu method |
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