Disease Identification System for Aura Images Using Fruit Fly Optimization (FAO) Technique

This chapter presents a novel methodology for disease identification acquired from the aura images of the individuals and endorsing the disease using the color image processing technique. The fruit fly optimization algorithm (FOA) is utilized for effectively identifying the feature vector using which the disease identification is carried out. The methodology is carried out using the Bio-Well benchmark data set and the results derived are subjected to evaluation based on qualitative metrics such as average difference (AD), minimum difference (MD), and image fidelity (IF). Image segmentation quality metrics are also considered, like the Probability Random Index (PRI), Global Consistency Error (GCE), and Volume of Information (VOI), to identify the accuracy of the segmentation procedure. The results derived showcase a good recognition accuracy of around 93%.