A New Algorithm to Stereo Correspondence Using Rank Transform and Morphology Based On Genetic Algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33093
A New Algorithm to Stereo Correspondence Using Rank Transform and Morphology Based On Genetic Algorithm

Authors: Razagh Hafezi, Ahmad Keshavarz, Vida Moshfegh

Abstract:

This paper presents a novel algorithm of stereo correspondence with rank transform. In this algorithm we used the genetic algorithm to achieve the accurate disparity map. Genetic algorithms are efficient search methods based on principles of population genetic, i.e. mating, chromosome crossover, gene mutation, and natural selection. Finally morphology is employed to remove the errors and discontinuities.

Keywords: genetic algorithm, morphology, rank transform, stereo correspondence

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1057679

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2172

References:


[1] P. moallem, K. faez, and J. haddadnia. Fast Edge-Based Stereo Matching Algorithms through Search Space Reduction. IEICE Trans. INF. & SYST, Vol.E85-D, No.11 (20021101) pp. 1859-1871, November 2002.
[2] P. Moallem and K. Faez. Effective Parameters in Search Space Reduction Used in a Fast Edge-Based Stereo Matching. Journal of Circuits, Systems, and Computers, 14(2): 249-266, 2005.
[3] P. Moallem, M. Ashorian, B. Mirzaeian, and M. Ataei. A Novel Fast Feature Based Stereo Matching Algorithm with Low Invalid Matching. WSEAS Transaction on Computers, Issue 3, Vol. 5, pp. 469 - 477, March 2006.
[4] Bobik, A.F., Intille, S.S., 1999. Large occlusion stereo. Int. J.Computer. Vis. 33, 181-200.
[5] Okutomi, M., Kanade, T., 1992. A locally adaptive window for signal matching. Int. J. Comput. Vis. 7, 143-162.
[6] Zhang, Y., Kambhamettu, C., 2002. Stereo matching with segmentation-based cooperation. In: Proc. of 7th European Conference on Computer Vision, pp. 556-571.
[7] Boykov, Y., Veksler, O., Zabih, R., 1997. Disparity component matching for visual correspondence. In: Proc. of International Conference on Computer Vision and Pattern Recognition, pp. 470-475.
[8] Szeliski, R., Scharstein, D., 2002. Symmetric sub-pixel stereo matching. In: Proc. of 7th European Conference on Computer Vision, pp. 525-540.
[9] C. Tomasi and R. Manduchi, "Stereo matching as a nearest Neighbor problem," IEEE Trans. Pattern Anal. Machine Intell., vol. 20, pp. 333- 340, Mar. 1998.
[10] K. Muhlmann, D. Maier, J. Hesser, and R. Manner. Calculating Dense Disparity Maps from Color Stereo Images, an Efficient Implementation. International Journal of Computer Vision, Volume 47, Issue 1-3, 79 - 88, 2001.
[11] S. Yoon, S.K. Park, S. Kang, and Y. K. Kwak. Fast correlation-based stereo matching with the reduction of systematic errors . Pattern Recognition Letters 26, 2221-2231, 2005.
[12] B. Tang, D. Ait-Boudaoud, B.J. Matuszewski, and L.k.Shark. An Efficient Feature Based Matching Algorithm for Stereo Images. Proceedings of the Geometric Modeling and Imaging-New Trends (GMAI-06), 195- 202, 2006.
[13] R.A.Lane and N.A.Thacker. Tutorial: Overview of Stereo Matching Research. Imaging Science and Biomedical Engineering Division, Medical School, University of Manchester, Stopford Building, Oxford Road, Cours, 1998.
[14] S.S. Tan and, D.P. Hart. A fast and robust feature-based 3D algorithm using compressed image correlation. Pattern Recognition Letters 26(11): 1620-1631, 2005.
[15] C. J. Taylor. Surface Reconstruction from Feature Based Stereo. Proceedings of the Ninth IEEE International Conference on Computer Vision (ICCV-03), Volume 2, 184,2003.
[16] Heijmans, H. J.A. M.: Morphological Image Operators. Academic Press (1994).
[17] http://vision.middlebury.edu/stereo/