International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Science , Computer Science and Engineering

Volume4,December 2017,

Topic : An Effective Approach for Diagnosis of Plant Disease using ELM

Authors:S.Vijayalakshmi || D.Murugan

Abstract:The objective of this paper is to identify the diseases in the leaves of all plants. The detection of disease is one of the crucial importance to increase the productivity of plants. Plant pathology is the scientific study of plant diseases, based on this study, to identify the pathogen, and classification under different kind of circumstances. In existing, the automatic plant disease detection without the training set using only prior knowledge. The proposed method, to use detects the diseases by using the ELM (Extreme Learning Machine) techniques. In the above method, initially, the ABC Clustering has approached for segments the affected area. Secondly, using TELP (Transform Encoded Local Pattern), Gradient Features, Color Histogram Techniques for extracting the features from that affected area. Finally, these extracted features are given to the ELM classifier to get the exact type of disease affected by a leaves.

Keywords: Plant Pathology, ABC clustering, TELP, ELM

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DOI: 01.1617/vol4/iss12/pid63541


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Editor-in-Chief

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Dr. Allon Guez
Professor, Drexel University,
USA


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IMPACT FACTOR: 4.890

ISSN(Online):2394-2320

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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ACCEPTANCE RATIO: 28.69%
ARTICLES PUBLISHED:0521
PAPER RECEIVED:01730
Journal Code : IJERCSE
Electronic ISSN : 2394-2320
Impact Factor : 4.890
Frequency : monthly
Contact : info@ijercse.com


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