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

机译:使用小程序通过感知空间进行彩色图像分割,以确定和预防辣椒中的疾病

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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.
机译:植物病原体引起植物疾病。辣椒是世界上最重要的农作物之一。当前有疾病检测技术,分类为:生化,显微镜,免疫学,核酸杂交,通过目视检查在体外还是在原位进行鉴定,但是它们具有以下缺点:它们需要几天的时间,其实施成本高且训练有素。本文提出了一种使用Java applet开发的在线系统通过彩色图像处理来了解和预防辣椒植物疾病的方法。该系统实时(远程)获得结果。图像被转换为​​感知空间[色相,饱和度和亮度(HSL),色相,饱和度和强度(HSI)和色相饱和度和值(HSV)]。将序列应用于所提出的方法。 HSI色彩空间是检测得最好的疾病。叶片中的疾病百分数为12.42%。与HSI颜色空间相比,HSL和HSV不会暴露疾病的确切区域。最后,对图像进行了分析,植物病理学专家知道该病采取了预防或纠正措施。

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