Since the corresponding pair of feature points was difficult to be extracted in feature points registration methods, an image mosaic method based on interest point matching was presented.
针对基于图像特征点的配准方法中对应特征对难以准确提取的问题，提出一种基于兴趣点匹配的图像自动拼接方法。
The detection of interest points is the basis of kinds of computer vision applications, such as: camera calibration, 3d reconstruction, image matching, video retrieval, motion estimation, etc.
兴趣点检测是许多计算机视觉应用的基础，如：摄像机定标、三维重建、图像匹配、视频检索、运动估计等。
Once the interest points were detected, the image matching process in an image sequence is performed using local gray-value differential invariants.
在获得了兴趣点之后，利用兴趣点处的局部灰度差分不变量进行序列图像的点特征匹配。
The geometry hashing technic is used to enhance the geometry constraint of interest points in order to improve the matching result.
通过几何哈希技术加强兴趣点间的几何约束，以增加正确匹配的兴趣点对数量。
The information available for image matching includes the gray-level of or near interest points and the geometrical relation of interest points.
利用兴趣点进行序列图像匹配可以利用兴趣点及其邻域的灰度信息和兴趣点集的几何信息。
The information available for image matching includes the gray-level of or near interest points and the geometrical relation of interest points.
利用兴趣点进行序列图像匹配可以利用兴趣点及其邻域的灰度信息和兴趣点集的几何信息。
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