| Computer & Information Science |
|
|
|
|
| Constrained branch-and-bound algorithm for image registration |
| JIN Jian-qiu, WANG Zhang-ye, PENG Qun-sheng |
| State Key Laboratory of CAD&CG, Zhejiang University, Hangzhou 310027, China; College of Computer & Information Engineering, Zhejiang Gongshang University, Hangzhou 310035, China; Department of Mathematics, Zhejiang University, Hangzhou 310027, China |
|
|
|
Abstract In this paper, the authors propose a refined Branch-and-Bound algorithm for affine-transformation based image registration. Given two feature point-sets in two images respectively, the authors first extract a sequence of high-probability matched point-pairs by considering well-defined features. Each resultant point-pair can be regarded as a constraint in the search space of Branch-and-Bound algorithm guiding the search process. The authors carry out Branch-and-Bound search with the constraint of a pair-point selected by using Monte Carlo sampling according to the match measures of point-pairs. If such one cannot lead to correct result, additional candidate is chosen to start another search. High-probability matched point-pairs usually results in fewer loops and the search process is accelerated greatly. Experimental results verify the high efficiency and robustness of the author’s approach.
|
|
Received: 02 February 2005
|
|
|
|
|
| [1] |
Brown, L.G., 1992. A survey of image registration techniques. ACM Computing Surveys, 24(4):326-376.
|
|
|
| [2] |
Chang, S.H., Cheng, F.H., Hsu, W.H., Wu, G.Z., 1997. Fast algorithm for point pattern matching: invariant to translations, rotations and scale changes. Pattern Recognition, 30(2):311-320.
|
|
|
| [3] |
Fischler, M.A., Bolles, R.C., 1981. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communication of the ACM, 24(6):381-395.
|
|
|
| [4] |
Frederick, S.H., Gerald, J.L., 1995. Introduction to Operation Research, 6th Edition. The McGraw-Hill Press, p.675-687.
|
|
|
| [5] |
Garder, W.F., Lawton, D.T., 1996. Interactive model-based vehicle tracking. IEEE Transaction Pattern Analysis and Machine Intelligence, 18(11):1115-1121.
|
|
|
| [6] |
Gavrilov, M., Indyk, P., Motwani, R., Venkatasubramanian, S., 1999. Geometric Pattern Matching: A Performance Study. Proc. 15th Annu. ACM Sympos. Comput. Geom., p.79-85.
|
|
|
| [7] |
Indyk, P., Motwani, R., Venkatasubramanian, S., 1999. Geometric Matching under Noise: Combinatorial Bounds and Algorithms. Proceedings of 10th Annual SIAM-ACM Symposium on Discrete Algorithms, p.457-465.
|
|
|
| [8] |
Price, K.E., 1985. Relaxation matching techniques A comparison. IEEE Transaction on Pattern Analysis and Machine Intelligence, 7(5):617-623.
|
|
|
| [9] |
Mount, D.M., Nathan, S., Netanyahu, J., Moigne, L., 1998. Improved Algorithms for Robust Point Pattern Matching and Applications to Image Registration. Proceedings of the Fourteenth Annual Symposium on Computational Geometry, Minneapolis, Minnesota, United States, p.155-164.
|
|
|
| [10] |
Pohl, C., van Genderen, J.L., 1998. Multisensor image fusion in remote sensing: concepts, methods and applications. International Journal of Remote Sensing, 19(5):823-854.
|
|
|
| [11] |
Rucklidge, W.J., 1995. Locating Objects Using the Hausdorff Distance. Proceeding of ICCV
|
|
|
| [12] |
Smith, S., Brady, J., 1997. SUSANA new approach to low level image processing. International Journal of Computer Vision, 23(1):45-78.
|
|
|
| [13] |
Zhang, Z., 1998. Determining the epipolar geometry and its uncertainty: A review. International Journal of Computer Vision, 27(2):161-195.
|
|
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
