Fuzzy Rule-Based Color Analysis for Skin Lesion Images

Fuzzy logic is a crucial topic that will bring fundamental changes to the medical field; it is a procedure to address uncertainty in cases with unclear medical images.This research focused on leveraging the features of fuzzy logic in efficiently analyzing the data and information contained in medical images and the ability to think and reason, owing to the facts and rules built into it, to obtain the required results.Skin diseases affect people worldwide.Providing healthcare and timely and accurate diagnoses of diseases are important.In the current era, artificial intelligence has emerged as a significant topic to analyze and diagnose skin diseases.This study examined eight medical images of patients with different skin diseases.Manual regions of interest were selected using the ImageJ system.Normal and diseased areas of equal size were selected, and their average colors (red, green, and blue) were measured.The values were then normalized.The difference between the normalized average color values of the normal and diseased areas was determined.Rules were proposed using fuzzy logic to analyze the results and identify the most distinctive color in the medical image.