In the above figures, Fig. 2, Fig. 3 and Fig. 4 show the variations of the green color from the healthy plant given in Fig. 1. These symptoms are a crucial part for extracting the features. The methodology begins by extracting the RGB indexes of different leaf samples and feeding the results to a database. The features include RGB values of the leaf and texture of the leaf. The texture helps to detect the water content in a leaf. Smoother the texture , higher the water content in a leaf. Apart from these two attributes, the feature extraction process can also extract holes or spots in a leaf which further helps as an indicator to potassium or phosphorous deficiency. Before entering the dataset , the image of the leaf is passed to through different Gaussian filters which removes the noise and any unwanted feature from the image. The basic outline of the image processing and feature extraction is given below.