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Tomato Plant Leaves Disease Classification Using KNN and PNN

Balakrishna K., Mahesh Rao

Source Title: International Journal of Computer Vision and Image Processing (IJCVIP)9(1)

ISSN: 2155-6997|EISSN: 2155-6989|EISBN13: 9781522567189|DOI: 10.4018/IJCVIP.2019010104

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MLA

Balakrishna K., and Mahesh Rao. "Tomato Plant Leaves Disease Classification Using KNN and PNN." IJCVIP vol.9, no.1 2019: pp.51-63. http://doi.org/10.4018/IJCVIP.2019010104

APA

Balakrishna K. & Rao, M. (2019). Tomato Plant Leaves Disease Classification Using KNN and PNN. International Journal of Computer Vision and Image Processing (IJCVIP), 9(1), 51-63. http://doi.org/10.4018/IJCVIP.2019010104

Chicago

Balakrishna K., and Mahesh Rao. "Tomato Plant Leaves Disease Classification Using KNN and PNN," International Journal of Computer Vision and Image Processing (IJCVIP) 9, no.1: 51-63. http://doi.org/10.4018/IJCVIP.2019010104

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Abstract

Plant diseases are a major threat to the productivity of crops, which affects food security and reduces the profit of farmers. Identifying the diseases in plants is the key to avoiding losses by proper feeding measures to cure the diseases early and avoiding the reduction in productivity/profit. In this article, the authors proposed two methods for identification and classification of healthy and unhealthy tomato leaves. In the first stage, the tomato leaf is classified as healthy or unhealthy using the KNN approach. Later, in the second stage, they classify the unhealthy tomato leaf using PNN and the KNN approach. The features are like GLCM, Gabor, and color are used for classification purposes. Experimentation is conducted on the authors own dataset of 600 healthy and unhealthy leaves. The experimentation reveals that the fusion approach with PNN classifier outperforms than other methods.

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Tomato Plant Leaves Disease Classification Using KNN and PNN

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