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Fuzzy Entropic Thresholding Using Gray Level Spatial Correlation Histogram

M. Seetharama Prasad*, C. Naga Raju**, L. S. S. Reddy***

* Singhania University, Pacheri Bari, Rajasthan, India.

** LBR College of Engineering, Mylavaram, India.

*** LBR College of Engineering, Mylavaram, India.

Periodicity:October - December'2011
DOI : https://doi.org/10.26634/jse.6.2.2894

Abstract

Threshold based segmentation is a popular technique in the preprocessing phase of image processing applications. In Abutaleb's two dimensional entropy, it is combined with local properties of the image to compute the optimal threshold. Yang Xiao et al. simplification on this procedure worked well with the inclusion of spatial correlation features which reduces the time complexity of the methodology. Seetharama Prasad et al. improvised further in the process of obtaining the varying similarity measure. In this paper fuzzy membership degrees of gray values are employed for conditional probabilities of the image object and background in the computation of entropy criterion function with local properties of the image as spatial correlation parameters are used in the obtainment of optimal threshold of the image. For low contrast images contrast enhancement is assumed. Experimental results demonstrate a quantitative improvement against existing techniques by calculating the parameter efficiency η based on the misclassification error and variations in various yielding towards ground truth threshold on two dimensional histogram of image.

Keywords

Entropy, GLSC Histogram, Threshold, Image Segmentation, Image Processing.

How to Cite this Article?

M. Seetharama Prasad, C. Naga Raju and LSS. Reddy (2011). Fuzzy Entropic Thresholding Using Gray Level Spatial Correlation Histogram. i-manager’s Journal on Software Engineering, 6(2), 20-30. https://doi.org/10.26634/jse.6.2.2894

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