The proposed algorithm relies on a group of new formulas for calculating tangent slope so as to address angle feature of edge curves of image. It can utilize tangent angle features to estimate automatically and fully ...The proposed algorithm relies on a group of new formulas for calculating tangent slope so as to address angle feature of edge curves of image. It can utilize tangent angle features to estimate automatically and fully the rotation parameters of geometric transform and enable rough matching of images with huge rotation difference. After angle compensation, it can search for matching point sets by correlation criterion, then calculate parameters of affine transform, enable higher-precision emendation of rotation and transferring. Finally, it fulfills precise matching for images with relax-tense iteration method. Compared with the registration approach based on wavelet direction-angle features, the matching algorithm with tangent feature of image edge is more robust and realizes precise registration of various images. Furthermore, it is also helpful in graphics matching.展开更多
It is shown that the polynomials based image registration, which is widely used in remote sensing field, does not have a sound mathematical basis. In fact, there seems no theoretical basis for the polynomials based tr...It is shown that the polynomials based image registration, which is widely used in remote sensing field, does not have a sound mathematical basis. In fact, there seems no theoretical basis for the polynomials based transform to outperform the affine transformation, a much simpler one,in image registration. If the transformation functions are polynomials of order n, the corresponding scene is shown to be in general the intersection of two curved surfaces of order n + 1, in other words,a space curve. In some special cases, the scene is approaching to a plane. To our knowledge, such results did not appear in the literature previously.展开更多
A new coarse-to-fine strategy was proposed for nonrigid registration of computed tomography(CT) and magnetic resonance(MR) images of a liver.This hierarchical framework consisted of an affine transformation and a B-sp...A new coarse-to-fine strategy was proposed for nonrigid registration of computed tomography(CT) and magnetic resonance(MR) images of a liver.This hierarchical framework consisted of an affine transformation and a B-splines free-form deformation(FFD).The affine transformation performed a rough registration targeting the mismatch between the CT and MR images.The B-splines FFD transformation performed a finer registration by correcting local motion deformation.In the registration algorithm,the normalized mutual information(NMI) was used as similarity measure,and the limited memory Broyden-Fletcher- Goldfarb-Shannon(L-BFGS) optimization method was applied for optimization process.The algorithm was applied to the fully automated registration of liver CT and MR images in three subjects.The results demonstrate that the proposed method not only significantly improves the registration accuracy but also reduces the running time,which is effective and efficient for nonrigid registration.展开更多
A new implementation of the image registration algorithm based on the mutual information is presented for the case of medical images. The registration is achieved if the maximum of the mutual information is attained. ...A new implementation of the image registration algorithm based on the mutual information is presented for the case of medical images. The registration is achieved if the maximum of the mutual information is attained. In this maximization process optimal values of five parameters of an affine transformation are searched.展开更多
The mean Hausdorff distance, though highly applicable in image registration, does not work well on partial matching images. An improvement upon traditional Hausdorff-distance-based image registration method is propose...The mean Hausdorff distance, though highly applicable in image registration, does not work well on partial matching images. An improvement upon traditional Hausdorff-distance-based image registration method is proposed, which consists of the following two aspects. One is to estimate transformation parameters between two images from the distributions of geometric property differences instead of establishing explicit feature correspondences. This procedure is treated as the pre-registration. The other aspect is that mean Hausdorff distance computation is replaced with the analysis of the second difference of generalized Hausdorff distance so as to eliminate the redundant points. Experimental results show that our registration method outperforms the method based on mean Hausdorff distance. The registration errors are noticeably reduced in the partial matching images.展开更多
为了提高运动目标轨迹分类的准确性,该文综合考虑了轨迹的位置信息和方向信息,提出了一种结合Hausdorff距离和最长公共子序列(Longest Common SubSequence,LCSS)的轨迹分类算法。该算法首先采用改进的Hausdorff距离对轨迹的位置信息进...为了提高运动目标轨迹分类的准确性,该文综合考虑了轨迹的位置信息和方向信息,提出了一种结合Hausdorff距离和最长公共子序列(Longest Common SubSequence,LCSS)的轨迹分类算法。该算法首先采用改进的Hausdorff距离对轨迹的位置信息进行相似性测量,然后采用改进的LCSS算法对轨迹的方向信息进行相似性测量。与其他轨迹聚类算法不同,该算法融合了Hausdorff距离和LCSS两种算法的优点,提高了轨迹分类的准确性。此外,为了进一步降低计算复杂度,该文还实现了一种基于插值的保距变换算法和一种LCSS快速算法。实验结果表明,该轨迹分类算法可以明显提高轨迹的聚类准确率,聚类准确率可达到96%;基于插值的保距变换算法和LCSS快速算法可以很大程度上降低算法的计算复杂度,下降幅度最大可达到80%。该方法可以同时满足轨迹分类对精确度、实时性和鲁棒性的要求。展开更多
基金Supported by the National Natural Science Foundation of China (No.60141002) the Aviation Basic Science Foundation (02I53073)
文摘The proposed algorithm relies on a group of new formulas for calculating tangent slope so as to address angle feature of edge curves of image. It can utilize tangent angle features to estimate automatically and fully the rotation parameters of geometric transform and enable rough matching of images with huge rotation difference. After angle compensation, it can search for matching point sets by correlation criterion, then calculate parameters of affine transform, enable higher-precision emendation of rotation and transferring. Finally, it fulfills precise matching for images with relax-tense iteration method. Compared with the registration approach based on wavelet direction-angle features, the matching algorithm with tangent feature of image edge is more robust and realizes precise registration of various images. Furthermore, it is also helpful in graphics matching.
基金Supported by National Natural Science Foundation of P. R. China (60175009, 60121302) Corresponding author:Hu Zhan-Yi
文摘It is shown that the polynomials based image registration, which is widely used in remote sensing field, does not have a sound mathematical basis. In fact, there seems no theoretical basis for the polynomials based transform to outperform the affine transformation, a much simpler one,in image registration. If the transformation functions are polynomials of order n, the corresponding scene is shown to be in general the intersection of two curved surfaces of order n + 1, in other words,a space curve. In some special cases, the scene is approaching to a plane. To our knowledge, such results did not appear in the literature previously.
基金Project(61240010)supported by the National Natural Science Foundation of ChinaProject(20070007070)supported by Specialized Research Fund for the Doctoral Program of Higher Education of China
文摘A new coarse-to-fine strategy was proposed for nonrigid registration of computed tomography(CT) and magnetic resonance(MR) images of a liver.This hierarchical framework consisted of an affine transformation and a B-splines free-form deformation(FFD).The affine transformation performed a rough registration targeting the mismatch between the CT and MR images.The B-splines FFD transformation performed a finer registration by correcting local motion deformation.In the registration algorithm,the normalized mutual information(NMI) was used as similarity measure,and the limited memory Broyden-Fletcher- Goldfarb-Shannon(L-BFGS) optimization method was applied for optimization process.The algorithm was applied to the fully automated registration of liver CT and MR images in three subjects.The results demonstrate that the proposed method not only significantly improves the registration accuracy but also reduces the running time,which is effective and efficient for nonrigid registration.
文摘A new implementation of the image registration algorithm based on the mutual information is presented for the case of medical images. The registration is achieved if the maximum of the mutual information is attained. In this maximization process optimal values of five parameters of an affine transformation are searched.
基金Project(61070090)supported by the National Natural Science Foundation of ChinaProject(2012J4300030)supported by the GuangzhouScience and Technology Support Key Projects,China
文摘The mean Hausdorff distance, though highly applicable in image registration, does not work well on partial matching images. An improvement upon traditional Hausdorff-distance-based image registration method is proposed, which consists of the following two aspects. One is to estimate transformation parameters between two images from the distributions of geometric property differences instead of establishing explicit feature correspondences. This procedure is treated as the pre-registration. The other aspect is that mean Hausdorff distance computation is replaced with the analysis of the second difference of generalized Hausdorff distance so as to eliminate the redundant points. Experimental results show that our registration method outperforms the method based on mean Hausdorff distance. The registration errors are noticeably reduced in the partial matching images.
文摘为了提高运动目标轨迹分类的准确性,该文综合考虑了轨迹的位置信息和方向信息,提出了一种结合Hausdorff距离和最长公共子序列(Longest Common SubSequence,LCSS)的轨迹分类算法。该算法首先采用改进的Hausdorff距离对轨迹的位置信息进行相似性测量,然后采用改进的LCSS算法对轨迹的方向信息进行相似性测量。与其他轨迹聚类算法不同,该算法融合了Hausdorff距离和LCSS两种算法的优点,提高了轨迹分类的准确性。此外,为了进一步降低计算复杂度,该文还实现了一种基于插值的保距变换算法和一种LCSS快速算法。实验结果表明,该轨迹分类算法可以明显提高轨迹的聚类准确率,聚类准确率可达到96%;基于插值的保距变换算法和LCSS快速算法可以很大程度上降低算法的计算复杂度,下降幅度最大可达到80%。该方法可以同时满足轨迹分类对精确度、实时性和鲁棒性的要求。
