基于稀疏特征点的零件图像拼接方法

针对纹理弱、特征稀少且存在大量相似性区域的零件图像拼接，一般基于特征点的图像拼接方法效果较差，本文提出一种改进方法。该方法首先依据FAST特征点检测方法提取特征点，再筛选出用于匹配的候选点集；其次，利用模板区域采样灰度特征，通过设置旋转角度和缩放比例搜索域结合结构相似性（SSIM）方法完成点匹配；最后，通过点匹配结果求出旋转、缩放和平移参量，利用3σ原则去除异常值得到最终结果。实验结果表明，在角度搜索域为［-45°,+45°］，缩放搜索域为［0.5,1.5］的条件下，本文方法能够得到较准确的旋转、缩放、平移参量及拼接效果。

A Part Image Mosaic Method Based on Sparse Feature Points

Aiming at the poor results that many image mosaic methods based on the feature points are used to parts image with weak texture, few features and many similar regions, an improved method is proposed. Firstly, the feature points are extracted by the FAST method, and the candidate points sets for matching are generated from them. Secondly, the gray feature values are sampled by template region, and the points matching results are obtained via setting the rotation angle and scaling search regions with the structural similarity index measurement (SSIM) method. Finally, the rotation, scaling, translation parameters are worked out by the points matching results. The last results of the parameters are gained through 3σ principle removing abnormal values. The experiment results show that the new method could get good rotation, scaling, translation parameters and mosaic image when angle search region is［-45°,+45°］ and scaling search region is［0.5,1.5］.