ABSTRACT
Considering that around 70 percent of India's population is dependent on agriculture, the country's economy is subject to substantial affects on agricultural yields as a result of environmental changes such as variations in temperature and rainfall. Anthracnose, which is caused by Colletotrichum, and leaf damage, which is caused by Alternaria alternata, are two examples of fungal diseases that can affect Phaseolus vulgaris L., which is a staple food legume for millions of people, and Camellia sinensis, which is a widely farmed non-alcoholic beverage crop. Both of these plants are very sensitive to fungal diseases. The objective of this research is to assist farmers by recognizing problems at an early stage and providing essential management information. This is accomplished through the utilization of sophisticated image processing algorithms for the automatic diagnosis of these diseases.
