Volume 10, Issue 2, October 2014, Pages 556–569
Reem Alattas1
1 Department of Computer Science & Engineering, University of Bridgeport, Bridgeport, CT, USA
Original language: English
Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Thresholding is one of the popular and fundamental techniques for conducting image segmentation. Many thresholding techniques have been proposed in the literature. Among them, the minimum cross entropy thresholding has been widely adopted. Most minimum cross entropy thresholding methods use Gaussian distribution as an ideal reference histogram for the images to be thresholded. Clearly, it is doubtful that any natural images would generate a histogram with such a distribution. In this paper, a new minimum cross entropy thresholding method using Gamma distribution is proposed, since it is more general than other distributions. The new entropy thresholding method using Gamma distribution is extended to multi-level thresholding. The experimental results manifest that the proposed method can derive multiple thresholds which are very close to the optimal ones. The convergence of the proposed method is analyzed mathematically and the results validate that the proposed method is efficient and is suited for different real time applications.
Author Keywords: thresholding, minimum cross entropy thresholding, multi-level thresholding, Gamma distribution, optical images thresholding.
Reem Alattas1
1 Department of Computer Science & Engineering, University of Bridgeport, Bridgeport, CT, USA
Original language: English
Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Thresholding is one of the popular and fundamental techniques for conducting image segmentation. Many thresholding techniques have been proposed in the literature. Among them, the minimum cross entropy thresholding has been widely adopted. Most minimum cross entropy thresholding methods use Gaussian distribution as an ideal reference histogram for the images to be thresholded. Clearly, it is doubtful that any natural images would generate a histogram with such a distribution. In this paper, a new minimum cross entropy thresholding method using Gamma distribution is proposed, since it is more general than other distributions. The new entropy thresholding method using Gamma distribution is extended to multi-level thresholding. The experimental results manifest that the proposed method can derive multiple thresholds which are very close to the optimal ones. The convergence of the proposed method is analyzed mathematically and the results validate that the proposed method is efficient and is suited for different real time applications.
Author Keywords: thresholding, minimum cross entropy thresholding, multi-level thresholding, Gamma distribution, optical images thresholding.
How to Cite this Article
Reem Alattas, “Multi-Level Minimum Cross Entropy Thresholding Using Gamma Distribution,” International Journal of Innovation and Scientific Research, vol. 10, no. 2, pp. 556–569, October 2014.
