关键词: Harris-Laplace, 冗余点, 尺度不变特征变换（SIFT）描述子, 图像配准

Abstract: Detected corner points using Harris-Laplace in multiple scales cause the problem that the same structure is detected in certain range of scales, which leads to finding many redundant points. Those points increase the complexity of computing in the later corner point description and matching procedure. Meanwhile, the difference of those points in scales and locations also causes mismatch. An improved Harris-Laplace method is proposed, which selects one characteristic point to represent the same local structure. With the improved Harris-Laplace method and SIFT descriptor, through setting the threshold of maximum and second maximum of distance, the auto image registration is realized. The results of many experiments compared with the original method indicate that the improved method not only has better invariant performance in image rotation transform illumination change and scale transform, but also can obtain stable matching pairs. Except that, for getting rid of many redundant points in detecting procedure, the consumed time of image registration and mismatch probability are also reduced.

Key words: Harris-Laplace, redundant points, Scale-Invariant Feature Transform（SIFT） descriptor, image registration