Plant Disease Identification and Classification using Image Processing
E.Vamsidhar1, P. Jhansi Rani2, K. Rajesh Babu3
1Dr. E.Vamsidhar, Associate Professor, Department of CSE, KL University, Vaddeswaram (A.P), India.
2P. Jhansi Rani, Associate Professor, Department of CSE, KL University, Vaddeswaram (A.P), India.
3K. Rajesh Babu, Associate Professor, Department of ECE, KL University, Vaddeswaram (A.P), India.
Manuscript received on 25 May 2019 | Revised Manuscript received on 03 June 2019 | Manuscript Published on 22 June 2019 | PP: 442-446 | Volume-8 Issue-3S, February 2019 | Retrieval Number: C10930283S19/19©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: An agricultural sector plays a vital role in the economy of country. Agricultural output is very vital in many developing countries. Increase in population and increase in the life expectancy is pressurizing the agricultural sector to come out with new types of high yielding crops. The diseases in the plants are common, early detection and controlling increases the yield of a crop. Development of technology in the field of computer science can be applied to detect these diseases early. Image processing and classification methods can be applied to identify the plant disease in the early stage. This paper developed a segmentation technique for automatic detection and classification of plant leaf diseases. Features are extracted and selected features are used for training and support vector machine (SVM) and artificial neural network (ANN) classifiers. The results obtained are satisfactory.
Keywords: Image Processing, CBIR, SVM, Plant Disease, ANN.
Scope of the Article: Signal and Image Processing