Constrained Compound Markov Random Field Model with Graduated Penalty Function for Color Image Segmentation

Abstract:

In this paper, an unsupervised color image segmentation scheme has been proposed for preserving strong and weak edges as well. A Constrained Compound Markov Random Field (MRF) has been proposed as the a priori model for the color labels. We have used Ohta (I1, I2, I3) color model and a controlled correlation of the color space has been accomplished by the proposed compound MRF model. The Constrained Compound MRF (CCMRF) is found to possess the unifying property of modeling scenes as well as color textures. In unsupervised scheme, the associated model parameters and the image labels are estimated recursively. The model parameters are the Maximum Conditional Pseudo Likelihood (MCPL) estimates and the labels are the Maximum a Posteriori (MAP) estimates. The performance of the proposed scheme has been compared with that of Yu’s method and has been found to exhibit improved performance in the context of misclassification error.

• Periodical: Advanced Materials Research (Volumes 403-408)
• Pages: 3438-3445
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.403-408.3438
• Online since: November 2011
• Authors: Sucheta Panda, P.K. Nanda
• Keywords: (I1, I2, I3) Color Space, MAP Estimate, Segmentation, Simulated Annealing (SA)

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[7] Sucheta Panda, P.K. Nanda, Unsupervised Color Image Segmentation using Constrained Compound MRF Model with Bi-Level Line Field", Proc. Of the IEEE sponsored International Conference on Advances in Computer Engineering (ACE, 2010), Bangalore, India, 21-22, June. 2010. (e) (f) Figure 1 : Segmentation of 'Ambeic liver abscess image' of size 500x400 (a) Original Image (b) Ground Truth (c) MRF optimized using Hybrid (d) CMRF optimized using hybrid(e) CCMRF optimized using hybrid (f) Clausi 's method (a) (b) (c) (d) (e) (f) Figure 2 : Segmentation of 'Cell image' of size 491x370 (a) Original Image (b) Ground Truth (c) MRF optimized using Hybrid (d) CMRF optimized using hybrid(e) CCMRF optimized using hybrid (f) Clausi 's method Figure 3 : Segmentation of 'Krishna River' Image of size 400x400 (a) Original Image (b) Ground Truth (c) MRF optimized using Hybrid (d) CMRF optimized using hybrid (e) CCMRF optimized using hybrid (f) Clausi , s method.

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