Examining Skin Images for Disease Diagnosis Using Statistical Analysis Combined with Machine Learning Techniques

Abstract

In the early stages of cancer, it is crucial to automatically monitor and analyze the condition. An essential characteristic that is included in the majority of dermoscopy algorithms is the presence of irregular streaks. These streaks are strongly associated with carcinoma and basal cell cancer. One of the most unpleasant and potentially dangerous diagnostic test techniques is used for detection.Unfortunately, this means that machine-driven detection is where our focus will be.In this case, we primarily want to implement the GLCM options for detection. Skin lesion options are derived using GLCMs, which are normalized symmetrical grey level co-occurrence matrices.textural options derived from GLCM A Multi-Class Support vector machine is used for classification purposes, and its input consists of square measures derived from each of the four classes.