Multiple macro nutrients deficiency identification using fuzzy C means

Abstract

Every plant needs nutrients for their growth. The leaf analysis in a plant can present the need of a nutrient to be determined. The macronutrients deficiency in plants can be identified by specific type of color variations using leaves image. Early identification of macronutrients can help plants in becoming suitable for the harvest and lessen the utilization of farm inputs. The proposed system implements a novel approach to identify the lack of nutrients in maize leaf images. The maize leaf images are collected from Agricultural University, Coimbatore. The input images are preprocessed where the images in RGB color space are converted to Lab model. Then C means clustering is used to segment the nutrient deficient part from leaf image. The multi-Color space based feature Extraction is used to extract the features from deficient area of maize leaf image and type of nutrients deficiency is identified using Fuzzy rule-based system that gives the percentage of nutrient deficiency affected in maize image. Then, the performance of this work is evaluated using confusion matrix.