SVM Classifier for Early Diagnosis of Malignant Melanoma

  • Puneet Kumar Goyal, Rati Shukla, Vikash Yadav, Dr. Nirvikar

Abstract

From recent years skin cancer has evolved as the most common among all other existing kind of cancers. The skin cancers include basal cell, melanoma and squamous cell cancer. Squamous and Basal cell are common and treatment of both is curable and very effective. On the other side, if allowed to grow, melanoma can extend quickly to rest parts of the body and could be almost incurable. If it is diagnosed and then treated in untimely stage, it becomes almost curable. Therefore a Computer Aided System is required to identify the skin cancer in its early stage and to diminish the rate of death of melanoma. In this paper, we propose a system which consists of various phases like image acquisition, image preprocessing, image segmentation, feature extraction and classification. We extract the features using GLCM and then these features are given to SVM classifier. It classifies the input image either into cancerous and non-cancerous image.

Published
2020-06-01
How to Cite
Puneet Kumar Goyal, Rati Shukla, Vikash Yadav, Dr. Nirvikar. (2020). SVM Classifier for Early Diagnosis of Malignant Melanoma. International Journal of Control and Automation, 13(02), 1344 - 1352. Retrieved from https://sersc.org/journals/index.php/IJCA/article/view/32912
Section
Articles