Image Segmentation Using Minimum Cross-Entropy Thresholding

Amani Al-Ajlan; Ali El-Zaart; IEEE

doi:10.1109/ICSMC.2009.5346619

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Conference proceeding

Image Segmentation Using Minimum Cross-Entropy Thresholding

Amani Al-Ajlan, Ali El-Zaart and IEEE

2009 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2009), VOLS 1-9, pp.1776-1781

IEEE International Conference on Systems Man and Cybernetics Conference Proceedings

01/01/2009

DOI: https://doi.org/10.1109/ICSMC.2009.5346619

Abstract

Computer Science

Computer Science, Cybernetics

Computer Science, Information Systems

Science & Technology

Technology

Entropy-based image thresholding is an important concept in the area of image processing. Pal (1996) proposed a minimum cross-entropy thresholding method based on Gaussian distribution. Our new method is derived from Pal method that segment images using minimum cross-entropy thresholding based on Gamma distribution and can handle bi-modal and multimodal images. Our method is tested by using Synthetic Aperture Radar (SAR) images and it gives reliable results for bimodal and multimodal images.

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Details

Title: Image Segmentation Using Minimum Cross-Entropy Thresholding
Creators - without role: Amani Al-Ajlan - King Saud University
Ali El-Zaart - King Saud University
IEEE
Publication Details: 2009 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2009), VOLS 1-9, pp.1776-1781
Series: IEEE International Conference on Systems Man and Cybernetics Conference Proceedings
Publisher: IEEE
Number of pages: 2
Identifiers: 9953194808331
Academic Unit: King Saud University
Language: English
Resource Type: Conference proceeding