从尺度不变特征变换算法的实时性与鲁棒性分析入手, 针对其在特征点匹配精度和匹配效率两方面不足, 提出一种基于运动目标的多尺度特征提取算法.该算法通过设计出一种基于尺度因子变化的高斯核模板尺寸自适应调整以及时间轴帧图像双向配准的办法, 成功地修正了运动目标图像配准的实时性与鲁棒性的不足.实验证明, 多尺度特征提取算法能够有效而快速地完成时间轴帧图像的特征点匹配.

Beginning with the analysis of the real-time performance and robustness of scale-invariant feature transform (SIFT), the paper optimized traditional algorithm in both aspects of matching time and accuracy. A multi-scale feature extraction algorithm was proposed which is based on moving target. This algorithm was devised in two improved ways. One way was that the size of the template could automatically adjust along with the change of the scale factor. The other was that a bidirectional feature points matching was introduced into the algorithm. With the improved algorithm, the weakness of the real-time performance and robustness was amended successfully for match between the images and the moving target. Finally, experiment showed that with the improved algorithm, the sequential frame images based on time-axis could be matched quickly and accurately.