Detection and Classification of Pests Using Neural Networks
P. V. Rama Raju1, P. M. P. Gayatri2, G. Nagaraju3
1P.V. Rama Raju, Department of Electronics and Communication Engineering, SRKR Engineering College, Bhimavaram (Andhra Pradesh), India.
2P.M.P.Gayatri, Department of Electronics and Communication Engineering, SRKR Engineering College, Bhimavaram (Andhra Pradesh), India.
3G. Nagaraju, Department of Electronics and Communication Engineering, SRKR Engineering College, Bhimavaram (Andhra Pradesh), India.
Manuscript received on 11 May 2019 | Revised Manuscript received on 05 June 2019 | Manuscript Published on 15 June 2019 | PP: 77-80 | Volume-8 Issue-1S3 June 2019 | Retrieval Number: A10150681S319/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Detection of pest is an essential factor to restrain serious outbreak in crops. Pest identification will not only add to the yield production but it is also a subsidiary for different types of agricultural practices or any sort of research. A common method for recognizing the pests is by naked eye observation. In this paper preprogrammed pest identification systems using various image processing techniques are presented. Initially, identifying and capturing the leaf with pest is done and in the subsequent steps techniques of image processing such as HSI conversion, segmentation, clustering, classifiers etc., are applied. Feature extraction is done on the area of interest of the segments. The results obtained are passed through neural network classifier. The neural network outperforms the task of classification of pest, disease or damage caused due to the presence of pest, medicine to cure the disease and the lifespan of pest.
Keywords: Clustering, HSI Conversion, Neural Networks, Segmentation.
Scope of the Article: Classification