An Organized Examination of Image Processing for Detection and Diagnosis of Plant Diseases

Agriculture is one of the most important and necessary sources of national wealth. Plant and crop diseases are one of the major factors that affect output quality and quantity. Lack of quality and quantity in food production creates a negative impact on the economy as well. Hence, it is crucial to identify plant diseases. Studies reveal a wide range of plant diseases occurring in different parts of the world. Various components of plants exhibit symptoms of plant diseases especially, the leaves. Extensive research is conducted across the globe and many horticulture specialists in liaison with technological experts apply computer vision and soft computing methods to automatically detect plant diseases from leaf photos. This article provides a summary of several aspects of such studies, along with their benefits and drawbacks. The authors addresses common infections as well as the state of such detection systems’ research at various stages. The current feature extraction methods are examined in order to determine which one seems to function best across a variety of crop categories. This study will aid researchers in their understanding of the use of computer vision for identifying and categorizing plant diseases.