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Automatic watershed segmentation of randomly textured color images

机译:随机纹理的彩色图像的自动分水岭分割

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A new method is proposed for processing randomly textured color images. The method is based on a bottom-up segmentation algorithm that takes into consideration both color and texture properties of the image. An LUV gradient is introduced, which provides both a color similarity measure and a basis for applying the watershed transform. The patches of watershed mosaic are merged according to their color contrast until a termination criterion is met. This criterion is based on the topology of the typical processed image. The resulting algorithm does not require any additional information, be it various thresholds, marker extraction rules, and suchlike, thus being suitable for automatic processing of color images. The algorithm is demonstrated within the framework of the problem of automatic granite inspection. The segmentation procedure has been found to be very robust, producing good results not only on granite images, but on the wide range of other noisy color images as well, subject to the termination criterion.
机译:提出了一种处理随机纹理彩色图像的新方法。该方法基于自底向上的分割算法,该算法同时考虑了图像的颜色和纹理属性。引入了LUV渐变,它提供了颜色相似性度量和应用分水岭变换的基础。分水岭马赛克的补丁根据它们的颜色对比进行合并,直到满足终止条件为止。该标准基于典型处理图像的拓扑。所得算法不需要任何附加信息,无论是各种阈值,标记提取规则等,因此都适合于彩色图像的自动处理。该算法在花岗岩自动检测问题的框架内得到了证明。已经发现分割过程非常鲁棒,不仅要在花岗岩图像上,而且要在终止准则的约束下,在各种其他嘈杂彩色图像上也能产生良好的结果。

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