Abstract: Agriculture plays the major role as it is big economic sector. However productivity of farm reduces by the plant diseases. Quality and quantity of plants also affected due to Different plant diseases, So Early detection plays vital role, to minimize the damage from plant diseases. The manual method for plant disease detection is poor, time consuming, uncertain and costly .Plant diseases are caused by bacteria, fungi and viruses. Fungal disease leads to sever damage to plant quality and productivity. There is fair amount of scope for plant disease detection in the area of agriculture. The recent computer vision and image processing based methods are quite primitive. Efficient image processing based method targeting towards better accuracy is a need of hour. Reliable, Robust and scalability factors needs to be considered while designing method for detecting plant diseases. Fungi disease detection of the leafy vegetables is first motivation of this research. Improving disease detection accuracy using optimized image processing algorithms. Along with leaf disease detection, crop detection and grading of disease is also important for automated system.
Keywords: Leaf disease, Image Processing, Segmentation, Feature Extraction, Classifiers
| DOI: 10.17148/IJARCCE.2019.8704