In the past, researchers and inspectors of fruit illnesses relied on the faulty human sight. The color shifts of the fruit stand in for the gestures. Color and pattern variances may serve as authenticity indicators in this case. Physical monitoring and detection of microorganisms, the next step in infection diagnosis, is an expensive, time-consuming process with limited accuracy. Therefore, the ideal option is to use certain methods in MATLAB that are more reliable than some other outmoded methods in order to make a very fast and error-free diagnostic. Lesions, infected fruit, and leaf spots all point to some kind of infection or illness affecting the plant. The goal of this assignment is to correctly identify the ailment from the provided photo. Image segmentation, preprocessing, feature extraction, and labeling are all essential steps. Bugs, the weather, and other elements of the environment may all play a role in the spread of infectious diseases including the flu, strep throat, and staph. In this scenario, we'll examine sickened fruit to find out what went wrong. In order to categorize the infection, we will extract picture features such as the fruit's main and minor axes.