The Transactions of the Korean Institute of Electrical Engineers D (대한전기학회논문지:시스템및제어부문D)

The Korean Institute of Electrical Engineers (대한전기학회)
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Robust Terrain Reconstruction Using Minimal Window Technique

최소 윈도우 기법을 이용한 강인한 지형 복원

  • 김동규 (명지대학교 정보공학과) ;
  • 우동민 (명지대학교 정보공학과) ;
  • 이규원 (대전대학교 컴퓨터 정보통신공학과)
  • Published : 2003.03.01
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Abstract

A stereo matching has been an important tool for the reconstruction of 3D terrain. The current state of stereo matching technology has reached the level where a very elaborate DEM(Digital Elevation Map) can be obtained. However, there still exist many factors causing DEM error in stereo matching. This paper propose a new method to reduce the error caused by the lack of significant features in the correlation window The proposed algorithm keeps the correlation window as small as possible, as long as there is a significant feature in the window. Experimental results indicate that the proposed method increases the DEM accuracy by $72.65\%$ in the plain area and $41.96\%$ in the mountain area over the conventional scheme. Comparisons with Kanade's result show that the proposed method eliminates spike type of errors more efficiently than Kanade's adaptive window technique and produces reliable DEM.

Keywords

References

  1. T. Kanade and M. Okutumi, 'A Stereo matching algorithm with adaptive windows: Theory and experiment', IEEE Trans. Pattern Anal. Machine Intell., vol. 16, no. 8, pp. 920-932, 1994 https://doi.org/10.1109/34.310690
  2. Bernd Jahne, Horst Haubecker, 'Handbook of Computer Vision and Applications', Academic Press. pp.411-449, 1999
  3. H. P. Moravec, 'Towards automatic visual obstacle avoidance', in proc. Int. Joint Conf. Artif. Intell., MA, 584
  4. Howard Schultz, 'Terrain reconstruction from widely separated images', University of Messachusetts, Department of Computer Science Amherst
  5. Jen-Luc Lotti, Gerard Giraudon, 'Adaptive Window Algorithm for Aerial Image Stereo', Pattern recognition, vol 1, pp. 701-703, 1994. 1 https://doi.org/10.1109/ICPR.1994.576410
  6. Jae-Chul Kim, Byoung-Ho Kang, Maeng-Sub Cho, 'Adaptive Hierarchical Stereo Matching Using Object Segmentation and Window Warping', IEEE International Conference on, vol. 4, pp. 2295-2300, 2001. 4 https://doi.org/10.1109/ICSMC.2001.972899
  7. Howard Schultz, Edward M. Riseman, Frank R.Stolle, Dong-Min Woo,' Error Detection and DEM Fusion Usinf SElf-Consistency' 7th IEEE International Conference on Computer Vision 1999, Sept https://doi.org/10.1109/ICCV.1999.790413
  8. M. J. Hannah, 'A system for digital stereo image matching', Photogrammetric Engineering and Remote Sensing, vol. 55, no. 12, pp. 1765-1770, 1989. 12
  9. R. C. Gonzalez and R. E. Woods, 'Digital image processing', Addison-Wesley Pub. Co, pp. 580-586, 1992
  10. Milan Sonka, Vaclav Hlavac, Roger Boyle. 'Image Processing Analysis and Machine Vision', PWS Pub. pp 448-483, 1998
  11. Howard Schultz, 'Terrain Reconstruction from Widely Separated Images', Proc. SPIE, Vol. 2486, pp. 113-123, 1995 https://doi.org/10.1117/12.213111
  12. 우동민, '적응적인 스테레오 정합 기법에 의한 3차원 지형 복원', 대한전기학회 논문집 47권 12호, pp. 2229- 2236,1998
  13. W. E. L. Grimson, 'Computational experiment with a feature based streo algorithm', IEEE Trans, Pattern Anal. Machine Intell., vol. 7, no. 1, pp. 17-34, 1985. 1 https://doi.org/10.1109/TPAMI.1985.4767615