针对Choi Wai pak等人提出的基于最大内切圆直方图的图像检索算法存在的不足，提出了一种改进的新的基于轮廓的图像检索算法。该算法首先用两种不同尺度的1维高斯函数分别对目标轮廓的凹陷部分和凸起部分进行进化处理来得到一个平滑简单而又能很好代表原始轮廓主要信息的进化曲线；然后利用骨架化算法提取出目标骨架；最后，利用进化后的轮廓与骨架之间的距离直方图来构造目标形状的描述符，并实现了图像检索。与Choi Wai pak等人提出的算法（只利用了形状的骨架信息）相比，该新算法不仅利用了轮廓所表达的外围整体形状信息，还利用了骨架所表达出的形状的拓扑关系。实验结果表明，该新算法在尺度变换、旋转变换以及抗噪性能等方面具有更优的鲁棒性。

In this paper, a contour based image retrieval algorithm is proposed for improving the algorithm proposed by Choi Wai pak et al, in which the shape of an object is represented based on the normalized maximal disks. In order to generate a simpler and smoother contour, the one dimensional Gaussian functions of two different scales are employed respectively for the concave and convex part of the contour in the proposed algorithm. Additionally, the skeleton of the contour is extracted by a skeletonization algorithm. Finally, the histogram of the distances between the evolved contour and skeleton is used to describe the shape for the retrieval purpose. As compared with the original algorithm that uses only the skeleton of an object, the algorithm proposed uses not only the contour that represents the shape of an object from outer but also the skeleton that preserves the original objects topology from inner. Experimental results show that the new algorithm proposed here outperforms that proposed by Choi Wai pak et al. in the robustness to the scaling, rotation and noise corruptions.