Fuzzy Based Visual Texture Feature for Psoriasis Image Analysis

Authors: G. Murugeswari, A. Suruliandi

Abstract:

This paper proposes a rotational invariant texture feature based on the roughness property of the image for psoriasis image analysis. In this work, we have applied this feature for image classification and segmentation. The fuzzy concept is employed to overcome the imprecision of roughness. Since the psoriasis lesion is modeled by a rough surface, the feature is extended for calculating the Psoriasis Area Severity Index value. For classification and segmentation, the Nearest Neighbor algorithm is applied. We have obtained promising results for identifying affected lesions by using the roughness index and severity level estimation.

Keywords: Fuzzy texture feature, psoriasis, roughness feature, skin disease.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1099882

References:

[1] Ahmed Fadzil M. H., Esa Prakasa, Hurriyatul Fitriyah, Hermawan Nugroho, Azura Mohd Affandi and S. H. Hussein, “Validation on 3D Surface Roughness Algorithm for Measuring Roughness of Psoriasis Lesion,” World Academy of Science, Engineering and Technology Vol.4 2010-03-25
[2] Ahmad Fadzil M Hani, Esa Prakasa, Hermawan Nugroho, Azura M Affandi and Suraiya H Hussein, “Body Surface Area Measurement and Soft Clustering for PASI Area Assessment,” Conf Proc IEEE Eng Med Biol Soc 2012:4398-401
[3] Ahmad Fadzil M. Hani, Esa Prakasa, Hurriyatul Fitriyah, Hermawan Nugroho, Azura Mohd Affandi and Suraiya Hani Hussein, “High Order Polynomial Surface Fitting for Measuring Roughness of Psoriasis Lesion,” Lecture Notes in Computer Science Volume 7066, 2011, pp 341-351
[4] Alexandru Caliman, Mihai Ivanovici and Noel Richard, “Colour Fractal Dimension for Psoriasis Image Analysis,” Proceedings of SPAMEC 2011, Cluj-Napoca, Romania, Pages 113-115
[5] J. Arrault, A. Arneodo, A. Davis, and A. Marsak, “Wavelet-based Multifractal Analysis of Rough Surfaces: Application to Cloud Models and Satellite Data,” Phys. Rev. Lett., Vol. 79, no. 1, pp. 75–79, July 1997
[6] Chaudhuri, B. B. and Sarkar, N “Texture Segmentation Using Fractal Dimension,” Pattern Analysis and Machine Intelligence, IEEE Transactions on (Volume: 17, Issue: 1 ) Jan 1995
[7] Chiranjeevi, P and S. Sengupta, “New Fuzzy Texture Features for Robust Detection of Moving Objects,” IEEE Signal Processing Letters, Vol. 19, No. 10, October 2012
[8] Dar-Ren Chen, Ruey-Feng Chang, Chii-Jen Chen, Ming-Feng Ho, Shou- Jen Kuo, Shou-Tung Chen, Shin-Jer Hung and Woo Kyung Moon, “Classification of Breast Ultrasound Images using Fractal Feature,”, Journal of Clinical Imaging 29 (2005),235-245
[9] Dimitrios Charalampidis and Takis Kasparis, “Wavelet-Based Rotational Invariant Roughness Features for Texture Classification and Segmentation,” IEEE Transactions on Image Processing, Vol. 11, No. 8, August 2002
[10] E-Liang Chen, Pau-Choo Chung, Ching-Liang Chen, Hong-Ming Tsai and Chein –I Chang, “An Automatic Diagnostic System for CT Liver Image Classification,” IEEE Transactions on Biomedical Engineering, Vol 45, No.6, June 1998
[11] Kalpan, L. M., “Extended Fractal Analysis for Texture Classification and Segmentation,” IEEE Transactions on Image Processing, Volume 8, Issue 11, Page (s):1572-1585, Nov. 1999
[12] J. M. Keller, S. Chen and R. M. Crownover, “Texture Description and Segmentation through Fractal Geometry,” Computer Vision, Graph, and Image Processing, Vol. 45, pp. 150-166, 1989
[13] E. G. Keramidas, D. K. Iakovidis and D. Maroulis, “Fuzzy Binary Patterns for Uncertainty-aware Texture Representation,” Electronic Letters on Computer Vision and Image Analysis 10(1): 63-78, 2011
[14] Khairul Muzzammil Saipullah, Nuraishah Sarimin and Nurul Atiqah Ismail, “A Fuzzy Texture Descriptor Using Combined Neighborhood Differences,” International Journal of Computer Science and Electronics Engineering (IJCSEE) Volume 1, Issue 3 (2013) ISSN 2320-401X; EISSN 2320-4028
[15] Lingmin He; Xiaobing Yang; Kangjian Wang and Lijun Peng, “Application of Improved Fuzzy Clustering Method in the Image Segmentation,” Fifth International Symposium on Computational Intelligence and Design (ISCID), 28-29 Oct. 2012, China,Volume:2, Page(s): 61- 64
[16] B. B. Mandelbrot and J. Van Ness, “Fractional Brownian Motion, Fractional Noise and Applications,” SIAM Review, Vol.10, 1968
[17] Manik Varma and Rahul Garg, “Locally Invariant Fractal Features for Statistical Texture Classification,”, IEEE 11th International Conference on Computer Vision, 14-21 Oct. 2007, Page (s):1-8
[18] Marcelo L. Alves, Esteban Clua and Fabiana R.Leta, “Evaluation of Surface Roughness Standards Applying Haralick Parameters and Artificial Neural Networks,” INSSIP 2012, 11-13 April 2012 Vienna, Austria
[19] Nidhal K. Al Abbadi, Nizar Saadi Dahir, Muhsin A. AL-Dhalimi and Hind Restom, “Psoriasis Detection Using Skin Color and Texture Features,” Journal of Computer Science 6 (6): 648-652, 2010, ISSN 1549-3636
[20] A. Pentland, “Fractal-based Description of Natural Scenes,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI- 6, pp. 666-674, 1984
[21] Rene Kamguem, Souheil Antoine Jahan and Victor Songmene, “Evaluation of Machined Part Surface Roughness using Image Texture Gradient Factor,” International Journal of Precision Engineering and Manufacturing, Vol. 14, No. 2, pp. 183-190
[22] Rocio A. Lizarraga-Morales, Raul E. Sanchez-Yanez and Victor Ayala- Ramirez, “Visual Texture Classification Using Fuzzy Inference,” 10th Mexican International Conference on Artificial Intelligence, 2011
[23] Savvas A. Chatzichristofis and Yiannis S. Boutalis, “FCTH: Fuzzy Color and Texture Histogram – A Low Level Feature for Accurate Image Retrieval,”, Ninth International Workshop on Image Analysis for Multimedia Interactive Services, 978-0-7695-3130-4/08 © 2008 IEEE
[24] Sebastien Deguy, Christophe Debain and Albert Benassi, “Classification of Texture Images using Multi-scale Statistical Estimator of Fractal Parameters,” British Machine Vision Conference 2000
[25] E. M. Srinivasan, Dr. K. Ramar and Dr. A. Suruliandi, “Rotation Invariant Texture Classification using Fuzzy Local Texture Patterns,” International Journal of Computer Science and Technology, Vol. 3, Issue 1, Jan-March 2012, Page (s): 653-657
[26] Volodymyr Mosorov and Lukasz Tomczak, “Image Texture Defect Detection Method Using Fuzzy C-Means Clustering for Visual Inspection Systems,” Arabian Journal for Science and Engineering, April 2014, Volume 39, Issue 4, pp 3013-3022
[27] Yong-xia, Feng, D.D. and Rong Chun-Zhao, “Morphology-based Multifractal Estimation for Texture Segmentation,” IEEE Transaction on Image Processing, Vol.15, Issue 3, March 2006 Page(s): 614-623
[28] Zhang Jian and Zhou Jin, “Surface Roughness Measure based on Average Texture Cycle,” Second International Conference on Intelligent Human Machine Systems and Cybernetics, 2010