基于特征点的图像拼接不仅不易受光照、旋转等因素影响,而且还有利于提高速度,是目前图像拼接的主流方向。尺度不变特征变换(SIFT)是目前比较成熟的一种角点检测算法,但是其特征点匹配问题仍然没有得到很好的解决。从系统相似的角度出发,提出了基于系统相似论的匹配准则,并将新匹配准则与传统的匹配准则进行了对比,指出了传统匹配准则存在的问题,测试了新准则匹配的精度和速度,分析了新准则能够取得更高精度的原因,并据新准则成功地检测了待拼接图像中的匹配角点,然后用改进的样本一致性算法计算出仿射变换的投影矩阵,并用Levenberg-Marquardt (L-M)算法对其求精,最终实现了图像的自动拼接。最后给出了全景相机图像的拼接结果,并对新的匹配准则给出了进一步的分析讨论。

The image stitching based on feature point is not only invulnerable to the light,rotation and other factors,but also helpful to increase efficiency. It has become one of the most attended methods. Scale invariant feature transform (SIFT) is a better coner extraction algorithm,but there are still some problems in the matching step. A new matching principle based on system similarity theory was proposed,and then it was compared with the traditional matching principle. The problems with tradtional matching principle was pointed out,and also the precision and speed of the new principle was tested ,and the reason why the new principle get higher precision was analysed. By the new principle the matching features were detected successfully. And then,the transform matrix was calculated by the progressive sample consistency algorithm. Further more,it was optimized by the Levenberg-Marquardt (L-M) algorithm,and finally automatic image stitching was realized . At last,the stiching result of panorama camera image was given,further discussion about the new matching principle was also given in the end of the paper.