Author(s): Ravikumar Chakali

Abstract: Pomegranate may be a fruit that grows with an awfully high yield in many nations of Asian countries and one in every one of the foremost profits gaining fruit within the market. However, because of numerous conditions, the plants are infected by numerous diseases that destroy the complete crop departure terribly less product yield. So, the work proposes a picture process and neural network strategies to agitate the most problems with Phytopathology, i.e. detection and classification of wellness. Pomegranate fruit is also attributed to the fact that. That leafs are affected by disease caused by plants and weather. These diseases are like blight microorganism, plant spots, seed places rot and leaf spot. The system uses some pictures for coaching, some for testing functions, and so on. The colour picture is pre-processing and endures k-means clustering segmentation. The feel options are extracted victimization the GLCM technique and given to the factitious neural network. The general accuracy of this technique is ninetieth. The results are well-tried to be correct and satisfactory in distinction to manual grading and hopefully, take a powerful rise in establishing itself within the market jointly of the foremost economical processes.

DOI: 10.33545/27075923.2020.v1.i2a.13

Pages: 08-10 | Views: 2591 | Downloads: 2180

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