• N.Jothy
• M.Ramani
• P.Vignesh Raj

The amount and proportion of chlorophyll present in the leaf is determined based on its color. The rate of chlorophyll in a leaf is the governing factor of a plant’s health and nutrient status. An insufficient amount of chlorophyll indicates an unhealthy plant growth and a poor nutrient status. Hence, the determination of the amount of Chlorophyll present in a leaf has become essential because farmers can apply the necessary fertilizers in order to achieve a proper plant growth and a good yield. At present researches, there are two approaches to measure the chlorophyll content: a destructive and a non-destructive method which are based on chemical analysis and by use of a hand held device respectively. These existing models have proved to be expensive and time consuming. To overcome these problems non-linear method is implemented. The chlorophyll content is estimated by Image processing using Gaussian process (GP). In addition to this leaf disease can be detected using K-means clustering algorithm and classified using SVM Classifier

Chlorophyll, Gaussian process, Image processing, K-means clustering, Non-Destructive, SVM.

"Detection of Leaf Disease and Estimation of Chlorophyll using K-means Algorithm and Gaussian Process", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 11, page no.156-163, November-2018, Available :http://www.jetir.org/papers/JETIR1811922.pdf

"Detection of Leaf Disease and Estimation of Chlorophyll using K-means Algorithm and Gaussian Process", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 11, page no. pp156-163, November-2018, Available at : http://www.jetir.org/papers/JETIR1811922.pdf