一种准确识别植物叶片病害的预处理方法

Deepa
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引用次数: 1

摘要

植物叶片病害检测在农业生产中具有十分重要的意义。如果不及早发现叶片病害,可能会影响产量。在任何图像处理应用中,图像预处理都是一个重要的步骤。植物叶片病害的检测采用了几种算法。但是,当这些算法用于有噪声的图像或在光线较差的条件下拍摄的图像时,往往不能产生预期的结果。由于噪声、照度差异、相机方位等因素,对这些图像进行预处理是必要的。图像的预处理有助于进一步的处理步骤。该方法首先对图像进行锐化处理,然后采用中值滤波进行去噪。然后使用k-means聚类对图像进行分割。结合这些方法,获得了较好的图像质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Pre Processing Approach for Accurate Identification of Plant Diseases in leaves
Detection of diseases in plant leaves is very crucial in agriculture. If the diseases in leaves are not identified at the initial stage it may affect the productivity. Pre processing the images is an important step in any image processing applications. Several algorithms are used to detect the diseases in plant leaves. But, when these algorithms are used for the noisy images or images taken under poor light conditions, they do not tend to generate expected result. Pre processing of these images becomes necessary because of noise, difference in illumination, camera orientation. Pre processing of images assists the further processing steps. In the proposed method the image is initially sharpened, and then Median filter is applied for denoising. The image is then segmented using k-means clustering. Combining these methods, better quality image was obtained.
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