Novel algorithm for segmentation and automatic identification of pests on plants using image processing

Enormous agricultural yield is lost every year, due to rapid infestation by pests and insects. A lot of research is being carried out worldwide to identify scientific methodologies for early detection/identification of these bio-aggressors. In the recent past, several approaches based on automation and image processing have come to light to address this issue. Most of the algorithms concentrate on pest identification and detection, limited to a greenhouse environment. Also, they involve several complex calculations to achieve the same. In this paper, we propose a novel and unique algorithm to segregate and detect pests using image processing. The proposed methodology involves reduced computational complexity and aims at pest detection not only in a greenhouse environment but also in a farm environment as well. The whitefly, a bio-aggressor which poses a threat to a multitude of crops, was chosen as the pest of interest in this paper. The algorithm was tested for several whiteflies affecting different leaves and an accuracy of 96% of whitefly detection was achieved. The algorithm was developed and implemented using MATLAB programming language on MATLAB 7.1 build 2011a.