• Akanksha Kale
• Pratiksha Gade
• Sheetal Gadge
• Sukanya Rajbhoj
• Prof. B. B. Vikhe

Nowadays in India Cotton is considered one of the most important cash crops i.e. White Gold, as most farmers cultivate cotton in large numbers. The diseases on cotton, over the past few decades, have lead to major loss of yield and productivity. Identification of cotton diseases at early stage diagnosis is important. The goal of our proposed work presents a system using a simple image processing techniques for the automatic diagnosis of cotton leaf diseases. Classifications based on selecting appropriate features such as color, the texture of images are done by using SIFT classifier. The images are acquired from cotton fields using a digital camera. Various preprocessing techniques as filtering, background removal, segmentation, binerisation, and enhancement are done. Color-based segmentation is done to obtain the diseased segmented part from the cotton leaf. A segmented image is used for feature extraction. This is one among the explanations that disease detection in plants plays a crucial role within the agriculture field, as having the disease in plants is sort of natural. Manual diagnosis of plant diseases needs expert knowledge alongside awareness. So, automatic disease detection and identification of plants by application of computer vision approaches are of utmost importance. During this paper, different computer vision approaches for disease detection are analyzed. The results demonstrate the effectiveness of varied methods in plant disease detection.

Image Processing, Leaf Disease Detection, Classification, Segmentation, Leaf Image, KNN Algorithm, SVM (Super Vector Machine), etc.

"Cotton Leaf Disease Detection using Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.a718-a723, June-2021, Available :http://www.jetir.org/papers/JETIR2106098.pdf

"Cotton Leaf Disease Detection using Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppa718-a723, June-2021, Available at : http://www.jetir.org/papers/JETIR2106098.pdf