• Suruchi Padhy
• Prof Sandeep Kumar

This paper describes the design and implementation of pragmatic system for detection of skin lesion using feature extraction techniques. The skin properties like skin dryness, fungus and allergic symptoms of skin layer may lead to starting symptoms of malignant melanoma skin cancer. The correct identification of skin spots based on certain features is the key steps in detecting the skin cancer disease in advance. The affected skin texture profile correlation with malignant melanoma skin cancer is discussed in the proposed work. Detection of skin cancer in earlier stages can be a lifesaving process. The detection of skin lesion includes four important stages namely Pre-processing, Segmentation, Feature Extraction and Classification. Detection can help in curing the cancer and hence detection plays a very vital role. In this paper, this system proposes two methods of preprocessing and features were extracted using GLCM. The KNN classifier, applied on extraction features which will classify image as melanoma and benign.

Skin lesion, Melanoma, Benign ,Gaussian filter, RGB channel, preprocessing, segmentation, thresholding, edge detection, feature extraction, K-Nearest Neighbor (KNN); Gray Level Co-occurrence Matrix (GLCM).

"Pragmatic System For Detection Of Skin Lesion Using Feature Extraction Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.64-74, June 2019, Available :http://www.jetir.org/papers/JETIR1906Y81.pdf

"Pragmatic System For Detection Of Skin Lesion Using Feature Extraction Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp64-74, June 2019, Available at : http://www.jetir.org/papers/JETIR1906Y81.pdf