International Journal of Image, Graphics and Signal Processing(IJIGSP)
ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)
Published By: MECS Press
IJIGSP Vol.7, No.6, May. 2015
Role of GLCM Features in Identifying Abnormalities in the Retinal Images
Full Text (PDF, 446KB), PP.45-51
Accurate detection of exudates in the diabetic retinal images is a challenging task. The images can have varying contrast and color characteristics. In this paper authors present the performance comparison of two feature extraction methods namely color intensity features and second order texture features based on GLCM. Authors have proposed and implemented new approach for GLCM feature calculation in which the input image is divided into number smaller blocks and GLCM features are computed on these blocks. The performance of each feature extraction method is evaluated using Back Propagation Neural Network (BPNN) classifier that is classifying the blocks as either abnormal block or normal block. With GLCM features, an accuracy of 76.6% was obtained and with color features an accuracy of 100% was obtained. It was found that color features are better in identifying true positives than GLCM based texture features. However use of GLCM features reduces the occurrence of false positives.
Cite This Paper
Shantala Giraddi, Jagadeesh Pujari, Shivanand Seeri,"Role of GLCM Features in Identifying Abnormalities in the Retinal Images", IJIGSP, vol.7, no.6, pp.45-51, 2015.DOI: 10.5815/ijigsp.2015.06.06
Akara Sopharak, "Comparative Analysis of Automatic Exudates Detection betauthorsen Machine Learning and Traditional Approaches", IEJCE Transaction of INF & SYST, VOL.E92-D.NO.11. 2009, pp 2264-2271.
H.F. Jaafar, A.K. Nandi and W. Al-Nauimy, "Automated detection of exudates in retinal images using a split-and-merge algorithm," EUSIPCO 2010, Alborg, pp. 1622-1626, 2010.
Ivan Soares, Miguel Castelo-Branco, Antonio M, G. Pinnheiro ," Exudates Dynamic Detection In Retinal Fundus Images Based On The Noise Map Distribution", 19th European Signal processing Conference 2011, pp 46-50.
Ram, K.; Joshi, G.Sivaswamy, J.A Successive Clutter-Rejection-Based Approach for Early Detection of Diabetic Retinopathy, Biomedical Engineering, IEEE Transactions on, Issue Date: March 2011.
Shahin E.M, Taha, T.E.; Al-Nuaimy W. " Automated detection of diabetic retinopathy in blurred digital fundus images ", 8th International conference on Computer Engineering Conference (ICENCO), Dec 29-30. 2012, pp 20 – 25.
Selvathi D, N.B.Prakash, Neethi Balagopal " Automated Detection of Diabetic Retinopathy for early diagnosis using feature extraction and Support vector machines ".
R.M. Haralick, K. Shanmugam, I. Dinstein, "Textural Features for Image Classification, IEEE Transactions of Systems, Man, and Cybernetics, vol. 3, no. 6, pp. 610–621, 1973.
B. Santhi and R. Seethalakshmi "Classifier in Age classification", Research Journal of Applied Sciences, Engineering and Technology 4(24): 5372-5374, 2012.
Abdolvahab Ehsanirad and Sharatkumar Y. H. " Leaf recognition for plant classification using GLCM and PCA methods", Oriental Journal of Computer Science & Technology, Vol. 3(1), 31-36 (2010).
Alaa Eleyani, Hasan DEM˙IREL2 Co-occurrence matrix and its statistical features as a new approach for face recognition" Turk J Elec Eng & Comp Sci, Vol.19, No.1, 2011, c_ T¨UB˙ITAK doi:10.3906/elk-0906-27.
Daljit Singh, Kamaljeet Kaur, "Classification of Abnormalities in Brain MRI Images Using GLCM, PCA and SVM", International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249 – 8958, Volume-1, Issue-6, August 2012.
Feroui Amel,Messadi Mohammed,Bessaid Abdelhafid , "Improvement of the Hard Exudates Detection Method Used For Computer- Aided Diagnosis of Diabetic Retinopathy", International Journal of Image, Graphics and Signal Processing (IJIGSP), Vol.4, No.4, May 2012.
Handayani Tjandrasa, Isye Arieshanti, Radityo Anggoro "Classification of Non-Proliferative Diabetic Retinopathy Based on Segmented Exudates using K-Means Clustering", IJIGSP Vol. 7, No. 1, December 2014.
Morium Akter, Mohammad Shorif Uddin "Morphology-Based Exudates Detection in Diabetic Retinopathy", ADVANCES IN BIOMEDICAL SCIENCE AND ENGINEERING Volume 1, Number 1, September 2014.
Alaa ELEYAN , Hasan DEM˙IREL, "Co- Occurrence matrix and its statistical features as a new approach for face recognition ", Turk J Elec Eng & Comp Sci, Vol.19, No.1, 2011, pp 97-107.