• Dr.M.Latha
• S.Jaya

Agriculture sector is one of the most important factor in our country which exports products like, fruits, vegetables, plants and ayurvedic medicines. Plants can be affected by fungal, bacterial and it cause to damage parts of the plant from top to bottom. It is very difficult to monitor and find the diseased plant manually. Image processing technology has been proved to be an efficient analysis to identify and detect the disease on a leaf. Identification of defected leaf is the way to preventing the loss occurred on agricultural product. This paper intends to focus on how image processing techniques are used to classify diseased leaf using preprocessing methods such as, k-means clustering, Segmentation using Canny Edge Detection, Threshold, Grabcut algorithm used for foreground extraction of the leaf and OpenCV Histogram is used to visualize graphical representation of a leaf. The proposed method seems to be the best image processing techniques to classify the diseased leaf and Python 3.7.1- OpenCV have been used as a programming tool for identification and classification of affected leaf in Image processing.

Image Processing, Segmentation, Canny Edge Detection, Grabcut Algorithm, Foreground Extraction

" IMAGE PROCESSING TECHNIQUES ON DISEASED LEAF: AN REVIEW ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.314-318, March-2019, Available :http://www.jetir.org/papers/JETIRAD06052.pdf

" IMAGE PROCESSING TECHNIQUES ON DISEASED LEAF: AN REVIEW ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp314-318, March-2019, Available at : http://www.jetir.org/papers/JETIRAD06052.pdf