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Pattern Recognition and Image Analysis

, Volume 20, Issue 1, pp 29–41 | Cite as

Images thresholding using ISODATA technique with gamma distribution

  • A. El-ZaartEmail author
Representation, Processing, Analysis, and Understanding of Images

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.

Keywords

Segmentation ISODATA Gamma distribution Splitting and merging Homogeneous test 

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Copyright information

© Pleiades Publishing, Ltd. 2010

Authors and Affiliations

  1. 1.Department of Computer Science, College of Computer and Information SciencesKing Saud UniversityRiyadhKingdom of Saudi Arabia

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