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PLANT DISEASE DETECTION USING PREWITT ALGORITHM AND NEURAL NETWORK IN IMAGE PROCESSING

J Navarajan M E, V Jeyaramya M E, R Oviya,A Monica and K Anandhalakshmi,
Department of ECE, Panimalar Institute of Technology, Chennai, India.

Abstract—The main objective of this paper is to determine the type of the disease that the leaf is infected using Image Processing. Plant diseases have turned into a dilemma as it can cause significant reduction in both quality and quantity of agricultural products. Now a day’s image processing technique is becoming a key technique for diagnosing the various features of the plants. The diseases can affect any part or area of the plants. In agriculture research of automatic leaf disease detection is essential research topic as it may prove benefits in monitoring large fields of crops, and detecting diseases on plant leaves. In this paper, the following methods are used, Prewitt algorithm for segmentation, GLCM for feature extraction and Neural Network for classification.

Index Terms—Prewitt algorithm, GLCM, Neural network

Cite: J Navarajan M E, V Jeyaramya M E, R Oviya, A Monica and K Anandhalakshmi, "PLANT DISEASE DETECTION USING PREWITT ALGORITHM AND NEURAL NETWORK IN IMAGE PROCESSING," International Journal of Electrical and Electronic Engineering & Telecommunications, Vol. 1, No. 1, pp. 1-7, March 2015.