IoT Based Skin Cancer Detection - A Systematic Survey

Authors

  • Dr. P. Thangara, Dr. A. Devipriya, Ms. Salomi Samsudeen, Dr. Vignesh V, Mr. Sahasranaman B

Abstract

In cancer, the most type of cancer is skin cancer, which affects the life of millions of people every year. In United States alone three million people are affected.The rate of survival decreases steeply as the disease progresses. In the early stages the detection of skin cancer was a difficult and expensive process. Here propose a methodology that detects and identifies skin lesions as benign or malignant based upon images taken from general cameras. The images are segmented, features extracted by applying the ABCD rule and a Neural Network is trained to classify the lesions to a high degree of accuracy. In the Feature extraction, digital image processing method includes symmetry detection, Border Detection, color, and diameter detection and also used to extract the texture based features. In this paper, proposes the SVM to classify the benign or malignant stage. One of the more frequently encountered cancers is Melanoma, which quite often depends on exposure to ultraviolet radiation occurring in solar radiation.

Published

2020-12-01

Issue

Section

Articles