GTCM Based Skin Lesion Melanoma Disease Detection Approach for Optimal Classification of Medical Images
K. Muthukumar1, P. Gowthaman2, M. Venkatachalam3, M. Saroja4, N. Pradheep5
1K. Muthukumar, Research Scholar, Department of Electronics, Erode Arts and Science College, Erode (Tamil Nadu), India.
2P. Gowthaman, Assistant Professor, Department of Electronics, Erode Arts and Science College, Erode (Tamil Nadu), India.
3L. Venkatachalam, Associate Professor, Department of Electronics, Erode Arts and Science College, Erode (Tamil Nadu), India.
4M. Saroja, Associate Professor, Department of Electronics, Erode Arts and Science College, Erode (Tamil Nadu), India.
5N. Pradheep, Research Scholar, Department of Electronics, Erode Arts and Science College, Erode (Tamil Nadu), India.
Manuscript received on 24 April 2019 | Revised Manuscript received on 03 May 2019 | Manuscript Published on 07 May 2019 | PP: 228-234 | Volume-7 Issue-6S3 April 2019 | Retrieval Number: F1046376S19/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The medical image classification plays vital role in the detection of various diseases. Number of approaches available for the detection of skin lesion melanoma but suffers to achieve higher performance. Towards this issue, a GTCM (Gray-Texture-Covariance-measure) based melanoma detection approach is presented in this paper. The method reads the input skin image and enhances by applying multi level gray filters. From the enhanced image, the method extracts gray features and texture features. The texture features of the lesion have been extracted based on the gray covariance matrix generated. Extracted features has been converted into GTC matrix and based on the values of GTC, the method estimates the GTCM measure towards the available training set. Finally based on the similarity of GTCM, the method estimates the GTC lesion strength to perform detection of melanoma. The method improves the performance of melanoma detection and reduces the false classification ratio.
Keywords: Skin Lesion, Melanoma, Medical Imaging, Image Classification, GTC.
Scope of the Article: Image Security