Color image segmentation using perceptual spaces through applets for determining and preventing diseases in chili peppers

Abstract

Plant pathogens cause disease in plants. Chili peppers are one of the most important crops in the world. There are currently disease detection techniques classified as: biochemical, microscopy, immunology, nucleic acid hybridization, identification by visual inspection in vitro or in situ but these have the following disadvantages: they require several days, their implementation is costly and highly trained. This paper proposes a method for knowing and preventing the disease in chili peppers plant through a color image processing, using online system developed in Java applets. This system gets results in real time and remotely (Internet). The images are converted to perceptual spaces [hue, saturation and lightness (HSL), hue, saturation, and intensity (HSI) and hue saturation and value (HSV)]. Sequence was applied to the proposed method. HSI color space was the best detected disease. The percentage of disease in the leaf is of 12.42%. HSL and HSV do not expose the exact area of the disease compared to the HSI color space. Finally, images were analyzed and the disease is known by the expert in plant pathology to take preventive or corrective actions.

Keywords: Applets, knowing disease, color image segmentation, perceptual spaces

African Journal of Biotechnology Vol. 12(7), pp. 679-688