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International Journal of Scientific Development and Research - IJSDR
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Issue: October 2019

Volume 4 | Issue 10

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Paper Title: Detection and Classification of Apple Fruit Diseases using K-means clustering and Learning Vector Quantization Neural Network.
Authors Name: Mr. Abhijeet Vishnu Jamdar , Prof.A.P.Patil
Unique Id: IJSDR1706064
Published In: Volume 2 Issue 6, June-2017
Abstract: In development of India there is major contribution of agricultural field. There are so many fruits that are exported from India and give more profit to the farmers. Diseases in fruit cause devastating problem in economic losses and production in agricultural industry. Manual identification of defected fruit is very time consuming. Web-based system used to help non experts in identifying fruit diseases, based on the picture representing the symptoms of the fruit. In this paper, we suggest a solution for the detection and classification of three common diseases on apple fruit (apple rot, apple scab, apple blotch). The image processing based proposed approach is composed of the three main steps; in the first step K-Means clustering segmentation algorithm is used for the image segmentation, in the second step some state of the art features are extracted from the segmented image, and finally images are classified into one of the classes by using Learning Vector Quantization Neural Network. Experimental results showed that the proposed system can significantly support accurate detection and automatic classification of apple fruit diseases. For the proposed solution we get more than 95% classification accuracy
Keywords: Apple Fruit Disease Detection and Classification
Cite Article: "Detection and Classification of Apple Fruit Diseases using K-means clustering and Learning Vector Quantization Neural Network.", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.2, Issue 6, page no.423 - 429, June-2017, Available :http://www.ijsdr.org/papers/IJSDR1706064.pdf
Downloads: 0001434
Publication Details: Published Paper ID: IJSDR1706064
Registration ID:170528
Published In: Volume 2 Issue 6, June-2017
DOI (Digital Object Identifier):
Page No: 423 - 429
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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