Crop Diseases In Agriculture

1250 Words5 Pages
Abstract: crop diseases may lead to severe agricultural yield. Hence classification and identification of crop diseases is essential to improve the agricultural yield. Various methods have been proposed to identifying the crop diseases, but the accuracy is considered to be issue over all the researches performed so far. In proposed system, the image is taken, preprocessing the image. The preprocessed image is subjected to K means clustering to get infected part of the leaf. The infected part is subjected to morphological processing to expanding the infected area. The infected part of leaf is subjected to histogram of oriented gradient (HOG) algorithm to extracted the features.SVM classifier is used to identify and classify the diseases based…show more content…
Agriculture sector plays a strategic role in the process of economic development of a country. It has already made a significant contribution to the economic prosperity of advanced countries and its play vital role in the economic development of less developed countries. Agriculture helps to gather the basic needs of human and their society by providing food, clothing, shelters, medicine and recreation. Agricultural development is multidirectional having galloping quickly and rapid extend with respect to time and space. After green revolution, farmers started using increase cultural practices and agricultural inputs in severe cropping systems with laborers intensive programmes to enhance the manufacturing potential per unit land, time and input. Agriculture is mainly depends on economic growth in India. Most of India families are immigration for most important work is agricultural. Gross domestic product in India, agricultural contribution about 16%. Agricultural production is not only rice. Agricultural product also includes rice, Wheat, potato, tomato, onion, mangoes, sugarcane, beans, cotton, etc. All people…show more content…
A. B. Ingole proposed approach for detected and classified the leaf diseases. This paper extracted the feature by converting RGB format in hue saturation. From the hue, saturation value extracted the future.Based on the feature classified the leaf diseases using artificial neutral network [4]. Prof. Sanjay B. Dhaygude, Mr. Nitin P. Kumbhar proposed the approach, extracted feature using the color co-occurrence method and evaluation diseases using texture statistics [5] Loyce Selwyn Pinto, Argha Ray, M. Udhayeswar Reddy, Pavithra Perumal, Aishwarya proposed the approach used to separate the infected part using K means clustering algorithm. After feature extraction classified the diseases using SVM [6]. Jagadeesh D. Pujari Rajesh Yakkundimath Abdulmunaf S.Byadgi proposed the approach used to extract the feature using gray level occurance matrix and classifying the crop diseases using nearest neighborhood classifier in classification algorithm [7]. P.Revathi, M.Hemalatha proposed the approach used to segment the infected part of image using edge detection. Classifying the diseases using Homogeneous Pixel Counting technique for Cotton Diseases Detection

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