Segmentation of the colour image is challenging because the colour information is lost after being projected into three channels of the colour space. Many state-of-the-art colour image segmentation methods are based on monochrome segmentation in one channel of the colour space. However, the optimal performance of a segmentation method usually could not be achieved in a single colour space due to the complexity and diversity of the colour images. In this study, the authors propose to segment the colour image by fusing the slope difference distribution (SDD) clustering results in different colour spaces. For simplicity, the segmentation approach is designed as two-label segmentation and it could be easily generalised to be multiple-label segmentation. The proposed approach is compared with the state-of-the-art colour image segmentation methods both quantitatively and qualitatively. Experimental results verified the effectiveness of the proposed approach.

中文翻译：

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通过融合来自不同色彩空间的SDD聚类结果，对彩色图像进行稳健的分割

彩色图像的分割具有挑战性，因为在将彩色信息投影到色彩空间的三个通道后会丢失它们。许多最新的彩色图像分割方法都是基于在色彩空间的一个通道中进行单色分割的。但是，由于彩色图像的复杂性和多样性，通常无法在单个色彩空间中实现分割方法的最佳性能。在这项研究中，作者建议通过融合不同颜色空间中的斜率差异分布（SDD）聚类结果对彩色图像进行分割。为简单起见，将分割方法设计为两标签分割，可以很容易地将其推广为多标签分割。将所提出的方法与最新的彩色图像分割方法进行了定量和定性的比较。实验结果证明了该方法的有效性。