中文摘要：

针对复杂场景中目标由于成像畸变、部分遮挡和局部缺失难于识别的难题，提出了一种新的特征点一弦高点，将其和遗传算法相结合用于图像的仿射配准．算法首先给出了弦高点的定义，并证明了其仿射不变性；然后，应用遗传算法搜索模型和目标轮廓上两对对应点，以弦高点作为第三对对应点，求解最优的仿射变换矩阵；最后，对遗传算法搜索的结果再进行线性搜索，提高配准的精度．本文利用LTS Hausdorff距离（Least trimmed square Hausdorff distance，LTS．HD）进行度量，能有效克服部分遮挡或局部缺失的影响．由于采用遗传算法，并只需搜索两对对应点，配准的速度得到提高．理论分析和实验结果均表明，该算法能有效地进行仿射配准，并能处理部分遮挡或局部缺失．

英文摘要：

It is difficult to recognize objects when they are distorted and partially occluded or broken. In order to solve the problems, a new registration algorithm combining chord height point with genetic algorithm is proposed in this paper. Firstly, we define the chord height point and prove it is affine invariant. Then, the global optimal affine transformation matrix is calculated by using three pairs of corresponding points, where two corresponding points in the contours of model and target are searched by the genetic algorithm, and the chord height point is used as the third pair of corresponding points. Finally, linear search is introduced to search the local optimal affine transform matrix, and the accuracy of registration is improved. We use least trimmed square Hausdorff distance （LTS-HD） to measure the similarity between the model and target, so our method can deal with object partially occlued and broken. Furthermore, the registration speed is improved by using genetic algorithm to search corresponding points and only searching two pairs of corresponding points. The theory analysis and experimental results show that our algorithm can be effectively used for affine registration, and can deal with objects partially occlued and broken.