中文摘要：

为解决彩色图像边缘检测中出现的RGB空间中向量排序、边缘准确定位以及抗噪性问题，提出一种基于形态学变形虫（自适应结构元素）并联合使用HSV空间和RGB空间的彩色图像边缘检测方法.首先在HSV空间中计算变形虫结构元素，克服了传统形态学结构元素选择不合理的缺点；然后借助HSV空间中的度量，并将其转换到RGB空间中完成向量的排序；再在RGB空间中，通过计算上述变形虫结构元素中像素间距离最小值定义边缘强度，不仅避免了HSV空间边缘定位不准确的问题，而且提高了算法的抗噪性；最后借用Canny算子的思想得到单像素边缘.实验结果表明，该方法能够充分考虑到图像的局部特征，边缘定位准确、抗噪效果显著，能得到有效、丰富的边缘信息.

英文摘要：

For solving the problems of the vector ordering in RGB space, edge location and denoising of the color image edge detection, a color image edge detection model based on the morphological amoebas （adaptive structuring elements） and RGB space and HSV space is presented. Firstly, the amoeba structural elements are calculated in the HSV space which overcomes the shortcomings of unreasonable selection of traditional morphological structure elements. Secondly, the vector ordering in RGB space is given according to the metric in HSV space. Thirdly, the edge intensity is defined in RGB space by calculating the minimum distance between pixels in the amoeba structural elements obtained, which not only avoids the inaccurate edge location in HSV space, but also improves the noise suppression. Finally, the idea of the Canny operator is used to get single pixel edge. The experimental results show that the proposed method can fully take into account the local features of an image edge and has the properties of accurate edge positioning and noise suppression.