| Summary: | Agriculture is the basis of every economy worldwide. Crop production is one of the major factors affecting domestic market condition in any country. Agricultural production is also a major prerequisite of economic development, be it any part of any country. It plays a crucial role as it even provides raw material, employment and food to different citizens. A lot of issues are responsible for estimated crop production varying in different parts of the world. Some of these include overutilization of chemical fertilizers, presence of chemicals in water supply, uneven distribution of rainfall, different soil fertility and others. Other than these issues one of the commonly faced challenges across the globe equally includes destruction of the major part of production due to diseases. After providing effective resources to the fields, major section of the production is diminished by the presence of diseases in the plants grown. This leads to focus on effective ways of detection of disease in plants. Presence of various diseases in plant is a major concern among farmers. Plant diseases acts as a major threat to small scale farmers as they lead to major destruction in overall food supply. To provide effective measures for detection and avoidance of the destruction requires an early identification of type of plant disease present. In recent time major work is being done for the identification of plant disease presents in varied parts of the world affection varied crops. Major work is being done in the domain of identification of causing factors of these diseases. Some of the diseases are marked by the presence of viruses while some are resultant of fungal infection. This becomes a major issue when the causing factor is not traceable before it has already spread to major production section. This paper brings a review on effective use of different imaging techniques and computer vision approaches for the identification and classification of plant diseases. Detection of Plant disease is initiated with image acquisition followed by pre-processing while using the process of segmentation. It is further accompanied by different techniques used for feature extraction along with classification. In this Paper we present the Current Trends and Challenges for detection of plant disease using computer vision and advance imaging technique.
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