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重采样和曲面拟合的图像匹配方法 被引量:2

A sub-pixel image matching method on re-sampling and curve fitting
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摘要 模式识别中的目标匹配和定位是一个传统问题,但是大多数经典算法其定位精度都是象素级的.图像的亚象元匹配算法,可以突破物理分辨率的限制,把匹配和定位精度从象素级提高到亚象元级,从而满足大规模集成电路制造、摄影测量、工业检测和目标检测等应用对精度的要求.将重采样方法和曲面拟合法有机结合的图像亚象元匹配方法,既有重采样方法精度高的优势,同时通过曲面拟合法加快了计算速度,减少了所需时间.实验结果证明了这种基于重采样和曲面拟合的图像亚象元匹配算法的有效性. The object matching and registration is a traditional problem in pattern recognition,but most typical algorithm of image registration is of pixel accuracy. A subpixel image matching algorithm with sub-pixel accuracy is described. The high precision image re-sampling speeded up by curve fitting algorithm is presented here, and its efficiency is proved by the experiments.
出处 《中国计量学院学报》 2006年第4期310-314,共5页 Journal of China Jiliang University
基金 浙江省自然科学基金资助项目(NO.Y109456) 浙江省科技厅重点项目(No.2005C21028)
关键词 图像匹配 亚象元 重采样 曲面拟合 image matching sub-pixel re-sampling curve fitting
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参考文献5

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二级参考文献4

  • 1DANIEL P HUTTENLOCHER,RYAN H LILIEN,CLARK F.View based recognition using an eigenspace approximation to the Hausdorff measure[J].Pattern Analysis and Machine Intelligence,1999,21(9):951-955.
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