• Dr. R. B. Dhumale
• N. D. Thombare
• Mr. Amit M Umbrajkaar
• A. N. Sarwade

Well-timed and precise leaf diseases classification of plant is the critical factors in agriculture. This leads to harm the crops and there may be financial losses in agriculture. Due to lack of knowledge in the leaf diseases of plant, farmers are using extreme pesticides. Plant diseases are microscopic in nature hence the diagnosis of plant disease is controlled by visual capabilities of human being. The visual nature of leaf disease classification emphasizes the computer visualization. This paper proposes a comparative study of leaf disease classification using Image Processing and Machine Learning Techniques. This approach of disease classification consists is implemented using RGB value Extraction and Disease Classification. The two diseases are classified viz. Whiteflies and Rust. The training database of leaf images consist input as RGB values of pixels and target values which indicates diseases of leaf like Healthy, Whiteflies and Rust. The different learning algorithms are discussed, trained and tested over 310 images. Comparison of disease classification is given for different classification techniques.

"Leaf Disease Classification using Machine Learning Approach ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.425-435, April-2019, Available :http://www.jetir.org/papers/JETIR1904L63.pdf

"Leaf Disease Classification using Machine Learning Approach ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp425-435, April-2019, Available at : http://www.jetir.org/papers/JETIR1904L63.pdf