• Mrs.A.Rajeswari

Skin cancer is the leading cause of death for people in the modern world. Skin cancer is an abnormal growth of skin cells that most frequently occurs on parts of the body that are exposed to sunlight. Early stages of the majority of skin malignancies can be cured Therefore, the patient's life can be saved by early and prompt detection of skin cancer. Early identification of skin cancer is now possible thanks to new technology. The biopsy procedure is the official way to diagnose skin cancer. Skin cells are removed, and the sample is then subjected to numerous laboratory tests. It takes a lot of time and is painful. For the early diagnosis of skin cancer disease, we have suggested an SVM-based skin cancer detection system. For the patients, it is better. A Support Vector Machine (SVM) algorithm and image processing techniques are used in the diagnosing methodology. A dermoscopy image of skin cancer is captured, then it is pre-processed using a variety of procedures to reduce noise and improve the image. The segmentation of the image is then performed using the Thresholding approach. The GLCM approach must be used to extract some visual features. These features are given as the input to the classifier. Support vector Machine (SVM) is a charity for classification purposes. It classifies the particular image into cancerous or non-cancerous.

Thresholding, SVM, GLCM, Digital Image, Classifier

"DETECTION AND CLASSIFICATION OF SKIN CANCER USING THE ABCD RULE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.150-155, March-2023, Available :http://www.jetir.org/papers/JETIRFV06028.pdf

"DETECTION AND CLASSIFICATION OF SKIN CANCER USING THE ABCD RULE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. pp150-155, March-2023, Available at : http://www.jetir.org/papers/JETIRFV06028.pdf