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Gradient Color Leaf Image Segmentation Algorithm Based on Meanshift and Kmeans

机译:基于VINSSHIFT和KMEANS的梯度彩叶图像分割算法

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In order to segment the gradient color leaf image accurately in complex background, a method of image segmentation combining meanshift algorithm and kmeans algorithm is proposed. In this paper, meanshift algorithm is used in LUV space to smooth the color image, then kmeans algorithm is used to divide and correct similar areas, and finally OTSU algorithm is used for image binary segmentation. The method uses the smoothing ability of meanshift algorithm to process the image gradient area, and uses the clustering ability of kmeans algorithm to solve the problem of under-segmentation of the gradient color region. The method can effectively separate the gradient color leaf image from different backgrounds. The results of the proposed method are better than the color index method.
机译:为了在复杂背景中精确地分割梯度彩色叶片图像,提出了一种图像分割组合速率算法和kmeans算法的方法。在本文中,意大利算法用于LUV空间以平滑彩色图像,然后使用kmeans算法划分和校正类似区域,最后使用Otsu算法用于图像二进制分割。该方法使用易换算法的平滑能力来处理图像梯度区域,并使用kmeans算法的聚类能力来解决梯度颜色区域的下分割问题。该方法可以有效地将梯度颜色叶图像与不同背景分开。所提出的方法的结果优于颜色指数方法。

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