Journal of the Institute of Electronics Engineers of Korea SP (대한전자공학회논문지SP)

The Institute of Electronics and Information Engineers (대한전자공학회)
권호 표지

Construction of 2D Image Mosaics Using Quasi-feature Point

유사 특징점을 이용한 모자이킹 영상의 구성

  • Kim, Dae-Hyeon (Dept.of Media Engineering, Gsaim Art Technology college, Chungang University) ;
  • Choe, Jong-Su (Dept.of Media Engineering, Gsaim Art Technology college, Chungang University)
  • 김대현 (중앙대학교 첨단영상대학원 영상공학과) ;
  • 최종수 (중앙대학교 첨단영상대학원 영상공학과)
  • Published : 2001.07.01
Download PDF
⟨ Previous Next ⟩

Abstract

This paper presents an efficient approach to build an image mosaics from image sequences. Unlike general panoramic stitching methods, which usually require some geometrical feature points or solve the iterative nonlinear equations, our algorithm can directly recover the 8-parameter planar perspective transforms. We use four quasi-feature points in order to compute the projective transform between two images. This feature is based on the graylevel distribution and defined in the overlap area between two images. Therefore the proposed algorithm can reduce the total amount of the computation. We also present an algorithm lot efficiently matching the correspondence of the extracted feature. The proposed algorithm is applied to various images to estimate its performance and. the simulation results present that our algorithm can find the correct correspondence and build an image mosaics.

본 논문은 영상 시퀸스로부터 이미지 모자이킹의 구성을 위한 효율적인 알고리즘을 기술한다. 영상의 기하학적인 특징을 이용하거나 비선형 방정식을 풀었던 기존의 알고리즘과는 달리, 제안한 알고리즘은 4개의 유사특징점을 이용해 영상간 사영 변환식의 8개 파라미터를 직접 계산한다. 본 논문에서 정의된 유사특징점은 영상의 그레이레벨의 분산을 기반으로 하고, 두 영상의 중첩 영역에서만 결정된다. 또한 선택된 4개의 유사특징점에 대한 대응점 검출을 위해 카메라 이동 및 조명 변화에 의한 영상의 변화를 고려한 블록 정합 알고리즘을 적용한다. 제안된 알고리즘은 다양한 영상에 적용하여 그 성능을 평가하였다. 모의 실험 결과는 제안된 알고리즘이 기존의 알고리즘에 비해 계산량을 감소시키면서, 정확한 사영 변환식을 유도하여 모자이킹 영상을 구성하는 것을 보여주고 있다.

Keywords

References

  1. R.Szeliski, 'Image Mosaicing for Tele-Reality applications,' IEEE Workshop on Applications of Computer Vision (WACV'94), pp. 44-53, Florida, December 1994 https://doi.org/10.1109/ACV.1994.341287
  2. R. Szeliski, H. Y. Shum, 'Creating full view panoramic image mosaics and environment maps,' Computer Graphics(SIGGRAPH'97), pp. 251-258, August 1997 https://doi.org/10.1145/258734.258861
  3. Z. Imad, O. Faugeras, R. Deriche, 'Using geometric ccorners to build a 2D mosaic from a set of images,' Proc. 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 420-425, Puerto Rico. June, 1997 https://doi.org/10.1109/CVPR.1997.609359
  4. R. Szeliski, S. B. Kang, 'Direct Methods for Visual Scene Reconstruction,' IEEE Wokrshop on Representations of Visual Scenes, pp. 26-33, Massachusetts, June 1995 https://doi.org/10.1109/WVRS.1995.476849
  5. L. G. Brown, 'A Survey of Image Registration Techniques,' ACM Computing Surveys, https://doi.org/10.1145/146370.146374
  6. B. S. Reddy, B. N. Chatterji, 'An FFT-Based Technique for Translation, Rotation and Scale-Invariant Image Registration,' IEEE Trans. on Image Processing, Vol.5 No.8 pp. 1266-1271, Aug. 1996 https://doi.org/10.1109/83.506761
  7. A. R. Weeks, Fundamentals of Electronic Image Processing, pp. 109-120, SPIE/IEEE Press, New York, 1996
  8. M. Tekalp, Digital Video Processing, pp. 95-116, Prentice Hall, Upper Saddle River, 1995
  9. Y. Hunag, X. Zhuang, 'An Adaptively Refined Block Mathching Algorithm for Motion Cormpensated Video Coding,' IEEE Trans. on Circuits Systems for Video Tech. Vol.5, no.1 pp. 56-59, Feb. 1995 https://doi.org/10.1109/76.350780
  10. H. M. Jong, L. G. Chen, T. D. Chiueh, 'Accuracy Improvement and Cost Reduction of 3-Step Search Block Matching Algorithm for Video Coding,' IEEE Trans. on Circuits/Systems for Video Tech. Vol.4, No.1 pp. 88-90, Feb. 1994 https://doi.org/10.1109/76.276175
  11. E. Trucco, A. Verri, Introductory Techniques for 3D Computer Vision, pp. 123-138, Prentice Hall, Upper Saddle River, 1998
  12. J. Goems, L. Velho, Image Processing for Computer Graphics, 247-296, Springer, New York, 1997