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Abstract: The Identification of pomegranate fruit disease (bacterial blight, scab etc.) and also the remedy for that disease after identification are proposed. Bacterial Blight disease needs to control at initial stages otherwise it makes economic loss to farmers. The captured image of the diseased fruit uploads to the system. The system then makes the image processing and makes the classification of fruit is infected. In Proposed system comparative accuracy analysis is done using K-means segmentation and also with different classifiers like PNN (Probabilistic Neural Network), KNN (K Nearest Neighbours’) and SVM (Support Vector machine). To achieve more accuracy closed capturing system, with high resolution camera is used, due to this capturing system 99% accuracy is achieved.
"Pomegranate Fruits Disease Classification with K Means Clustering", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.3, Issue 3, page no.74 - 80, March-2018, Available :http://www.ijrti.org/papers/IJRTI1803012.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator