A novel algorithm for segmentation of diseased apple leaf images

Abstract

The In Agriculture Sciences, detection of diseases is one of the most challenging tasks Sometimes agricultural experts need to take help of various sources to identify the diseases of plants. The misinterpretations of plant diseases often lead to wrong decision making, resulting in damage of crops. Hence the automatic recognition of the diseases by monitoring the indications on the plant leaves makes it less complicated as well as economical. For this proper segmentation of diseased part form the leaf in an accurate way is of utmost importance. This paper presents an algorithm for the segmentation of ROI region using image processing technique in the diseased apple leaf images. In this study, two different apple diseases which appears on leaves, namely Marsonina Coronaria and Apple Scab were chosen. The proposed segmentation algorithm is implemented on the enhanced leaves images by using enhancement technique of Binary Preserving Dynamic Fuzzy Histogram Equalization. The segmentation was carried out with a proposed background removal algorithm combined with K means clustering for apple. � 2018, Institute of Advanced Scientific Research, Inc.. All rights reserved.