目的 为解决目前大多数寻找最佳拼接缝的算法只考虑到对应像素的差异最小，却忽略了保留图像中目标的完整性，从而导致镶嵌结果中目标特性的破坏和图像信息损失的问题，提出一种基于8邻域内各像素到目标距离最短的寻找最佳拼接缝方法。方法 首先将形态学处理后的二值化图像划分为背景与目标；然后以尽量不切割目标为标准，将与目标距离最短的点作为拼接点；最后得到最佳拼接缝。结果 本文算法找到的最佳拼接缝使得图像的结构相似度和邓氏关联度都得到提高，错位程度降低5%以上。结论 相比于目前常用的寻找最佳拼接缝算法，本文算法能够更好地保留目标的完整性，错位现象基本消除，视觉上的灰度突变也有所减弱，图像质量得到明显改善，达到令人满意的视觉效果。

Objective We try to solve the problem that most algorithms only emphasize on the minimum difference between pixels rather than the integrity of objects for finding the optimal seam-line. Therefore, the mosaicking result will cause damages to objects and information loss in images. Method We put forward a novel algorithm for finding the optimal seam-line based on the shortest distance between the targets and each pixels in the 8-neighborhood. First,the image is divided into the targets and the background the morphological processing. Then, the closest points to the target are found as the splice points according to the rule of avoiding cutting the target. The optimal seam-line is finally retrieved by linking all the splice points. Result The seam-line retrieved by the algorithm proposed in this paper improves the structure similarity and correlation. The dislocation degree is also reduced by more than 5%. Conclusion This algorithm keeps the integrity of the targets better than the conventional algorithms. Obvious dislocations are removed and the gray mutation is weakened visually. The quality of image is improved and the result image reaches a satisfying effect.