arrow
Volume 5, Issue 2
Image Rectification Algorithm Based on Immune Monoclonal Strategy

Liansheng Sui, Xiaomei Yang, Jiulong Zhang

J. Info. Comput. Sci. , 5 (2010), pp. 109-116.

Export citation
  • Abstract
To rapidly and accurately search the corresponding points along scan-lines, rectification of stereo image pairs are performed so that all the epipolar lines are parallel to the horizontal scan-lines and the vertical difference between the corresponding epipolar lines is zero. According to the layered rectification algorithm presented by charles loop, we can divide the process of rectification into three steps including projective transformation, affine transformation and shearing transformation. The key to proposed algorithm is the computation of projective matrix, the algorithm uses the affine epipolar geometry constraint to compute projective matrix and determines the optimal value of unknown parameters in projective matrix by immune monoclonal strategy. In the process of solving the matrix, the algorithm does not require the relative matrix be positive definite. The experiments show that the proposed algorithm is an effective image rectification algorithm and it has the obvious advantage in mean vertical difference, distortion and speed of rectification.
  • AMS Subject Headings

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address
  • BibTex
  • RIS
  • TXT
@Article{JICS-5-109, author = {Liansheng Sui, Xiaomei Yang, Jiulong Zhang}, title = {Image Rectification Algorithm Based on Immune Monoclonal Strategy}, journal = {Journal of Information and Computing Science}, year = {2024}, volume = {5}, number = {2}, pages = {109--116}, abstract = { To rapidly and accurately search the corresponding points along scan-lines, rectification of stereo image pairs are performed so that all the epipolar lines are parallel to the horizontal scan-lines and the vertical difference between the corresponding epipolar lines is zero. According to the layered rectification algorithm presented by charles loop, we can divide the process of rectification into three steps including projective transformation, affine transformation and shearing transformation. The key to proposed algorithm is the computation of projective matrix, the algorithm uses the affine epipolar geometry constraint to compute projective matrix and determines the optimal value of unknown parameters in projective matrix by immune monoclonal strategy. In the process of solving the matrix, the algorithm does not require the relative matrix be positive definite. The experiments show that the proposed algorithm is an effective image rectification algorithm and it has the obvious advantage in mean vertical difference, distortion and speed of rectification. }, issn = {1746-7659}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22718.html} }
TY - JOUR T1 - Image Rectification Algorithm Based on Immune Monoclonal Strategy AU - Liansheng Sui, Xiaomei Yang, Jiulong Zhang JO - Journal of Information and Computing Science VL - 2 SP - 109 EP - 116 PY - 2024 DA - 2024/01 SN - 5 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jics/22718.html KW - image rectification,affine epipolar geometry,immune monoclonal strategy AB - To rapidly and accurately search the corresponding points along scan-lines, rectification of stereo image pairs are performed so that all the epipolar lines are parallel to the horizontal scan-lines and the vertical difference between the corresponding epipolar lines is zero. According to the layered rectification algorithm presented by charles loop, we can divide the process of rectification into three steps including projective transformation, affine transformation and shearing transformation. The key to proposed algorithm is the computation of projective matrix, the algorithm uses the affine epipolar geometry constraint to compute projective matrix and determines the optimal value of unknown parameters in projective matrix by immune monoclonal strategy. In the process of solving the matrix, the algorithm does not require the relative matrix be positive definite. The experiments show that the proposed algorithm is an effective image rectification algorithm and it has the obvious advantage in mean vertical difference, distortion and speed of rectification.
Liansheng Sui, Xiaomei Yang, Jiulong Zhang. (2024). Image Rectification Algorithm Based on Immune Monoclonal Strategy. Journal of Information and Computing Science. 5 (2). 109-116. doi:
Copy to clipboard
The citation has been copied to your clipboard