Identification of plant diseases based on images derived from computer vision is a major requirement for smart agriculture. Conventional algorithms warrant large dataset for better accuracy. They perform well with large variation in color or explicit probes on a specific disease. This paper considers 4 major diseases of cotton plants with a combination of images with and without color variation. This paper adapted image processing algorithms to extract precise features for classification, highly preferred and apt, when the dataset sizes are limited. Verification results of the proposed method validate its rationale and viability. ©BEIESP.
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A. R. Kommareddy, Polisetty, S. A., Kurra, C. S., Padmavathi, S., and Pokuri, M. C., “Image based identification of leaf crumple and leaf spot diseases in cotton plant”, International Journal of Recent Technology and Engineering, vol. 8, pp. 345-348, 2019.