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CLC number: TP391.41

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Received: 2005-02-02

Revision Accepted: 2005-06-12

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Journal of Zhejiang University SCIENCE A 2005 Vol.6 No.100 P.94~99


Constrained branch-and-bound algorithm for image registration

Author(s):  JIN Jian-qiu, WANG Zhang-ye, PENG Qun-sheng

Affiliation(s):  State Key Laboratory of CAD&CG, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   jqjin@cad.zju.edu.cn, zywang@cad.zju.edu.cn, peng@cad.zju.edu.cn

Key Words:  Image registration, Branch-and-Bound, Constrained refinement

JIN Jian-qiu, WANG Zhang-ye, PENG Qun-sheng. Constrained branch-and-bound algorithm for image registration[J]. Journal of Zhejiang University Science A, 2005, 6(100): 94~99.

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T1 - Constrained branch-and-bound algorithm for image registration
A1 - JIN Jian-qiu
A1 - WANG Zhang-ye
A1 - PENG Qun-sheng
J0 - Journal of Zhejiang University Science A
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SP - 94
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DOI - 10.1631/jzus.2005.AS0094

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.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


[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.

[14] Zitova, B., Flusser, J., 2003. Image registration methods: A survey. Image and Vision Computing, 21(11):977-1000.

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