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OALib Journal期刊
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Fast image registration method based on local salient feature
基于局部显著特征的快速图像配准方法

Keywords: scale invariant feature transform(SIFT),improved K-means algorithm,salient feature,salient region
尺度不变特征变换
,改进K-means聚类算法,显著特征点,显著区域

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Abstract:

Aiming at the problems such as large number of feature points, difficulty in accurate control, low computation speed and registration accuracy in SIFT algorithm, this paper presented a fast image registration method based on local salient feature. In the algorithm, it firstly down sampled the original input and reference images to reduce spatial resolution, then extracted the SIFT feature points from the down sampled images and clustered by the improved K-means algorithm. Subsequently, it obtained the clustered regions by filtering the above clustered results, extracted and matched the salient feature points coarsely in the clustered regions. Finally, it located the salient regions according to the matched salient point pairs and matched to achieve accurate registration. Experiment results show that the method can reduce the matching time, control the number of the feature points, and also improve the efficiency significantly when keeping a higher matching precision.

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