Pixel-based classification method for detecting unhealthy regions in leaf images

Abstract

In this paper, we present a pixel-based, discriminative classification algorithm for automatic detection of unhealthy regions in leaf images. The algorithm is designed to distinguish image pixels as belonging to one of the two classes: healthy and unhealthy. The task is solved in three steps. First, we perform segmentation to divide the image into foreground and background. In the second step, support vector machine (SVM) is applied to predict the class of each pixel belonging to the foreground. And finally, we do further refinement by neighborhood-check to omit all falsely-classified pixels from second step. The results presented in this work are based on a model plant (Arabidobsis thaliana), which forms the ideal basis for the usage of the proposed algorithm in biological researches concerning plant disease control mechanisms.