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Images thresholding using ISODATA technique with gamma distribution

  • Representation, Processing, Analysis, and Understanding of Images
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Abstract

Image segmentation is a fundamental step in many applications of image processing. Many image segmentation techniques exist based on different methods such as classification-based methods, edge-based methods, region-based methods, and hybrid methods. The principal approach of segmentation is based on thresholding (classification) that is related to thresholds estimation problem. The ISODATA (Iterative Self-Organizing Data Analysis Technique) method is one of the classification-based methods in image segmentation. We assumed that the data in images is modeled by Gamma distribution. The objective of this paper is to explain a new method that combines Gamma distribution with the technique of ISODATA. The algorithm has two phases: splitting using Gamma distribution then merging which are done based on some predefined parameters. Experimental results showed good segmentation for artificial and real images.

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Authors and Affiliations

  1. Department of Computer Science, College of Computer and Information Sciences, King Saud University, P.O. Box 51178, Riyadh, 11543, Kingdom of Saudi Arabia

    A. El-Zaart

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  1. A. El-Zaart
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Correspondence to A. El-Zaart.

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Ali El-Zaart was a senior software developer at Department of Research and Development, Semiconductor Insight, Ottawa, Canada during 2000–2001. From 2001 to 2004, he was an assistant professor at the Department of Biomedical Technology, College of Applied Medical Sciences. Since 2004, he is an assistant professor at the Department of Computer Science, College of computer and information Sciences. He has published numerous articles and proceedings in the areas of image processing, remote sensing, and computer vision. He received a B.Sc. in computer science from the University of Lebanon; Beirut, Lebanon in 1990, M.Sc. degree in computer science from the University of Sherbrooke, Sherbrooke, Canada in 1996, and Ph.D. degree in computer science from the University of Sherbrooke, Sherbrooke, Canada in 2001. His research interests include image processing, pattern recognition, remote sensing, and computer vision.

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El-Zaart, A. Images thresholding using ISODATA technique with gamma distribution. Pattern Recognit. Image Anal. 20, 29–41 (2010). https://doi.org/10.1134/S1054661810010037

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