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Volume 36 Issue 9
Sep.  2010
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Journal of Beijing University of Aeronautics and Astronautics  > 2010  >  36(9): 1121-1124.
Liu Jian, Zhang Guohua, Huang Linlinet al. Image registration approach based on improved SIFT[J]. Journal of Beijing University of Aeronautics and Astronautics, 2010, 36(9): 1121-1124. (in Chinese)
Citation: Liu Jian, Zhang Guohua, Huang Linlinet al. Image registration approach based on improved SIFT[J]. Journal of Beijing University of Aeronautics and Astronautics, 2010, 36(9): 1121-1124. (in Chinese)
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Image registration approach based on improved SIFT

  • 1.

    School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

  • 2. Key Laboratory of National Defense on Fire Control Technology, Luoyang Institute of Electro-optic Equipment, Luoyang 471004, China

  • 3. School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

  • Received Date: 10 Aug 2009
  • Publish Date: 30 Sep 2010
    Abstract
  • To resolve the problem of large angle and large scale image registration, an improved approach based on scale invariant feature transform (SIFT) is proposed. The log-polar technique was applied to estimate the parameters of rotations scales between reference image and sensed image. The images were segmented into sub-blocks and six candidates of sub-blocks were extracted according to information entropy, where SIFT features and moment features were fused to form a new feature descriptor. The image registration result was calculated from the matching points which were obtained by combining the Euclidean distance and the algorithm of iterative procrustes. The experimental results show that the proposed method is fast with high-precision.

     

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  • [1] Zitova B,Flusser J.Image registration method: a survey [J].Image and Vision Computing,2003,21:977-1000 [2] 张少辉,沈晓蓉,范耀祖.一种基于图像特征点提取及匹配的方法[J].北京航空航天大学学报,2008,34(5):516-519 Zhang Shaohui,Shen Xiaorong,Fan Yaozu.Method in image-s feature extraction and matching[J].Journal of Beijing University of Aeronautics and Astronautics,2008,34(5):516-519(in Chinese) [3] Lowe D G.Distinctive image features from scale-invariant keypoints [J].International Journal of Computer Vision,2004,60(2):91-110 [4] 王俊卿,史泽林,黄莎白.一种改进的不变矩的图像匹配算法[J].模式识别与人工智能,2005,18(2):228-233 Wang Junqing,Shi Zelin,Huang Shabai.An improved image matching algorithm based on moment invariant [J].Pattern Recognition and Artificial Intelligence,2005,18(2):228-233(in Chinese) [5] Wiernga J,Dijksterhuis G,Gower J,et al.Generalised Procrustes analysis with optimal scaling:exploring data from a power supplier[J].Computational Statistics and Data Analysis,2009,53:4546-4554
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