Optimizing Leaf Diseases of Apple Scab and Apple Black Rot in the Context of “Useful” Information Measures and Distance Measurements

Abstract

Detecting disease on crops is an essential and time-consuming operation in agricultural techniques. It takes a significant amount of time and specialized effort. This research provides a clever and effective agricultural disease detection system based on information theory. In the present chapter, first information measures, ‘useful' information measures, and distance measures are defined and explained. The authors find out the distance measures between leaves of apple scab (AS) and apple black rot (ABR). Six leaves of AS and ABR are taken into consideration. After measuring the distance, the impact of disease in the leaves of AS and ABR has been noticed. It is shown that this measure can be embedded in most image classification techniques and is subject to reference transformation. Weak and strong information is also obtained. Finally, minimum and maximum distances are evaluated, and our findings indicate that the likelihood of illnesses in plant leaves is low when the information measure of leaves is low.