Pest Detection and Identification by Applying Color Histogram and Contour Detectionby Svm Model
P. Ashok1, J. Jayachandran2, S.Sankara Gomathi3, M.Jayaprakasan4
1P.Ashok, Assistant Professor, Department of CSE, Sri Sai Ram Institute of Technology, Chennai (Tamil Nadu), India.
2J.Jayachandran, Assistant Professor, Department of CSE, Sri Sai Ram Institute of Technology, Chennai (Tamil Nadu), India.
3S.Sankara Gomathi, Professor, Department of ECE, Veltech Multitech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai (Tamil Nadu), India.
4M.Jayaprakasan, Joint Director, Directorate of Training, MSDE, Govt of India, (New Delhi), India.
Manuscript received on 25 May 2019 | Revised Manuscript received on 03 June 2019 | Manuscript Published on 22 June 2019 | PP: 463-467 | Volume-8 Issue-3S, February 2019 | Retrieval Number: C10970283S19/19©BEIESP
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Abstract: Insect Pest take a heavy toll on agricultural crops causing severe loss to the farmers and farming community.. Crops were damaged by attack of disease, insect, nematodes and weeds.. Our crops are under threat from the day they are seeded till they are harvested causing significant damage to the crop affecting adversely to the farmer’s economy. Many factors influence disease development and growth of insect that includes genetics of variety, plant growth stage, weather, soil and nutrients of plants form leaves and fruits etc. Developing a mobile app having a complete knowledge base of insect pest in the farmer’s field based on the damaged system or by the image of the insects through Image Processing technique. With this technique we introduce the SVM in Machine Learning for image classification and Color histogram and Contour Detection for feature extraction, K-fold and Bootstrapping algorithm for validation.
Keywords: Machine Learning, SVM, Color Histogram, Contour Detection, Open CV.
Scope of the Article: Probabilistic Models and Methods