Research Area:  Machine Learning
The symptoms of plant diseases are evident in different parts of a plant; however leaves are found to be the most commonly observed part for detecting an infection. Researchers have thus attempted to automate the process of plant disease detection and classification using leaf images. Several works utilized computer vision technologies effectively and contributed a lot in this domain. This manuscript summarizes the pros and cons of all such studies to throw light on various important research aspects. A discussion on commonly studied infections and research scenario in different phases of a disease detection system is presented. The performance of state-of-the-art techniques are analyzed to identify those that seem to work well across several crops or crop categories. Discovering a set of acceptable techniques, the manuscript highlights several points of consideration along with the future research directions. The survey would help researchers to gain understanding of computer vision applications in plant disease detection.
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Author(s) Name:  Sukhvir Kaur, Shreelekha Pandey & Shivani Goel
Journal name:  Archives of Computational Methods in Engineering
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Publisher name:  Springer
DOI:  10.1007/s11831-018-9255-6
Volume Information:   volume 26, pages: 507–530
Paper Link:   https://link.springer.com/article/10.1007/s11831-018-9255-6