%0 Journal Article %1 noauthororeditor %A K. Ramya Thamizharasi1, J.Ganesh2 %D 2019 %J Advances in Engineering: an International Journal (ADEIJ) %K Dermoscopy Histogram Melanocyte %N 3 %P 10-16 %T RECOGNITION OF SKIN CANCER IN DERMOSCOPIC IMAGES USING KNN CLASSIFIER %U https://airccse.com/adeij/papers/2319adeij02.pdf %V 2 %X The largest organ of the body is human skin. Melanoma is a fastest growing & deadliest cancer which starts in pigment cells (melanocytes) of the skin that mostly occurs on the exposed parts of the body. Early detection is vital in treating this type of skin cancer but the time and effort required is immense. Dermoscopy is a non invasive skin imaging technique of acquiring a magnified and illuminated image of a region of skin for increased clarity of the spots on the skin The use of machine learning and automation of the process involved in detection will not only save time but will also provide a more accurate diagnosis. The skin images collected from the databases cannot be directly classified by the automation techniques. The reason is twofold: (a) Lack of clarity in the features which is mainly due to the poor contrast of the raw image and (b) Large dimensions of the input image which causes the complexity of the system. Hence, suitable techniques must be adopted prior to the image classification process to overcome these drawbacks. The first drawback can be minimized by adopting suitable pre- processing techniques which can enhance the contrast of the input images. The second drawback is solved by incorporating the feature extraction technique which reduces the dimensions of the input image to high extent. Further, K-NN (K-Nearest Neighbor) classifier is used for classification of the given image into cancerous or non- cancerous.

@article{noauthororeditor, abstract = {The largest organ of the body is human skin. Melanoma is a fastest growing & deadliest cancer which starts in pigment cells (melanocytes) of the skin that mostly occurs on the exposed parts of the body. Early detection is vital in treating this type of skin cancer but the time and effort required is immense. Dermoscopy is a non invasive skin imaging technique of acquiring a magnified and illuminated image of a region of skin for increased clarity of the spots on the skin The use of machine learning and automation of the process involved in detection will not only save time but will also provide a more accurate diagnosis. The skin images collected from the databases cannot be directly classified by the automation techniques. The reason is twofold: (a) Lack of clarity in the features which is mainly due to the poor contrast of the raw image and (b) Large dimensions of the input image which causes the complexity of the system. Hence, suitable techniques must be adopted prior to the image classification process to overcome these drawbacks. The first drawback can be minimized by adopting suitable pre- processing techniques which can enhance the contrast of the input images. The second drawback is solved by incorporating the feature extraction technique which reduces the dimensions of the input image to high extent. Further, K-NN (K-Nearest Neighbor) classifier is used for classification of the given image into cancerous or non- cancerous.}, added-at = {2019-06-03T09:16:11.000+0200}, author = {K. Ramya Thamizharasi1, J.Ganesh2}, biburl = {https://www.bibsonomy.org/bibtex/29adc6a372a63350572120aa78d47821a/adeij_journal}, interhash = {608c7cb9e367de03cdbc1fc1b1bb3a9a}, intrahash = {9adc6a372a63350572120aa78d47821a}, journal = {Advances in Engineering: an International Journal (ADEIJ)}, keywords = {Dermoscopy Histogram Melanocyte}, month = may, number = 3, pages = {10-16}, timestamp = {2019-06-03T09:16:11.000+0200}, title = {RECOGNITION OF SKIN CANCER IN DERMOSCOPIC IMAGES USING KNN CLASSIFIER}, url = {https://airccse.com/adeij/papers/2319adeij02.pdf}, volume = 2, year = 2019 }