Translated Titles

Image Registration Using an Ant Colony Foraging Algorithm with Mutual Information





Key Words

影像套合 ; 蟻群最佳化演算法 ; 互資訊 ; 磁振影像 ; 空拍圖 ; Image registration ; ant colony optimization ; mutual information ; magnetic resonance image ; aerial image



Volume or Term/Year and Month of Publication


Academic Degree Category




Content Language


Chinese Abstract


English Abstract

Image registration is very important for a wide variety of image processing applications in engineering and medicine. It provides lots of image information for further analysis in many fields. There are many image registration methods being proposed. This thesis describes a new image registration algorithm using an ant colony optimization (ACO) approach. There are two fundamental properties in the proposed ACO process: the probabilistic transition and the pheromone update. We used the ACO algorithm to solve the direction and distance of advancement and combined linear interpolation to transform images. Thanks to the efficient ACO, complex calculation such as solving the Navier–Stokes partial differential equation is not necessary. The entropy condition in information theory was introduced to obtain interactive information in order to improve registration accuracy and reduce processing time. A wide variety of images including aerial images and medical images were used to evaluate this new method. Experimental results indicated that the proposed method efficiently performed registration and provided high accuracy. Comparing to the viscous fluid model method, our algorithm produced higher correlation coefficient scores but also spent less computation time. We believe that our algorithm is of potential in many image registration applications.

Topic Category 基礎與應用科學 > 海洋科學
工學院 > 工程科學及海洋工程學研究所
工程學 > 工程學總論
  1. [1] J. Modersitzki, Numerical methods for image registration: Oxford university press, 2003.
  2. [2] A. K. Jain, Fundamentals of digital image processing: prentice-Hall Englewood Cliffs, 1989.
  3. [3] M. D. Roger P. Woods. "AIR - Automated Image Registration," http://bishopw.loni.ucla.edu/air5/.
  4. [4] D. L. Wang H, O'Daniel J, Mohan R, Garden AS, Ang KK, Kuban DA, Bonnen M, Chang JY, Cheung R., “Validation of an accelerated 'demons' algorithm for deformable image registration in radiation therapy.,” Physics in Medicine and Biology, 2005.
  5. [5] W. R. Crum, T. Hartkens, and D. Hill, “Non-rigid image registration: theory and practice,” The British Journal of Radiology, 2014.
  6. [8] H. Zhang, Y. Sun, B. Zhai, and Y. Wang, “Ant colony optimization image registration algorithm based on wavelet transform and mutual information,” in Fifth International Conference on Digital Image Processing, 2013, pp. 88781J-88781J-6.
  7. [9] W. Wei, W. Lin, L. Liu, and Z. Q. Hu, “2D-3D Medical Image Registration Based on Ant Colony Algorithm,” in Applied Mechanics and Materials, 2014, pp. 267-273.
  8. [10] R. C. Gonzalez, and R. E. Woods, Digital image processing. 2002: publishing house of electronics industry, 2002.
  9. [13] R. M. Haralick, and L. G. Shapiro, “Image segmentation techniques,” in 1985 Technical Symposium East, 1985, pp. 2-9.
  10. [15] J. B. A. Maintz, and M. A. Viergever, “A survey of medical image registration,” vol. 2, pp. 36, 1998.
  11. [16] B. Zitova, and J. Flusser, “Image registration methods: a survey,” ELSEVIER, 2003.
  12. [18] J.-P. Thirion, “Image matching as a diffusion process: an analogy with Maxwell's demons,” Medical image analysis, vol. 2, no. 3, pp. 243-260, 1998.
  13. [20] H.-H. Chang, and C.-Y. Tsai, “Adaptive registration of magnetic resonance images based on a viscous fluid model,” Computer Methods and Programs in Biomedicine, vol. 117, no. 2, pp. 80-91, 2014.
  14. [22] C. G. Morten Bro-nielsen “Fast Fluid Registration of Medical Images,” 1996.
  15. [25] M. Dorigo, V. Maniezzo, A. Colorni, and V. Maniezzo, “Positive feedback as a search strategy,” 1991.
  16. [26] M. Dorigo, and L. M. Gambardella, “Ant colony system: a cooperative learning approach to the traveling salesman problem,” Evolutionary Computation, IEEE Transactions on, vol. 1, no. 1, pp. 53-66, 1997.
  17. [27] 楊郁仙, “基於螞蟻演算法與路口延滯時間之最短時間路徑規劃,” 中興大學資訊科學與工程學系所學位論文, pp. 1-49, 2013.
  18. [29] M. Dorigo, and L. M. Gambardella, “Ant colonies for the travelling salesman problem,” BioSystems, vol. 43, no. 2, pp. 73-81, 1997.
  19. [30] P. Huang, H. Cao, and S. Luo, “An artificial ant colonies approach to medical image segmentation,” Computer Methods and Programs in Biomedicine, vol. 92, no. 3, pp. 267-273, 2008.
  20. [31] J. Edmonds, “Matroids and the greedy algorithm,” Mathematical programming, vol. 1, no. 1, pp. 127-136, 1971.
  21. [32] F. Maes, D. Vandermeulen, and P. Suetens, “Comparative evaluation of multiresolution optimization strategies for multimodality image registration by maximization of mutual information,” Medical image analysis, vol. 3, no. 4, pp. 373-386, 1999.
  22. [35] E. D'Agostino, F. Maes, D. Vandermeulen, and P. Suetens, “A viscous fluid model for multimodal non-rigid image registration using mutual information,” Medical image analysis, vol. 7, no. 4, pp. 565-575, 2003.
  23. [6] W. Peng, R. Tong, G. Qian, and J. Dong, "A constrained ant colony algorithm for image registration," Computational Intelligence and Bioinformatics, pp. 1-11: Springer, 2006.
  24. [7] H. Rezaei, M. Shakeri, S. Azadi, and K. Jaferzade, “Multimodality image registration utilizing ant colony algorithm,” in Machine Vision, 2009. ICMV'09. Second International Conference on, 2009, pp. 49-53.
  25. [11] 洪維恩, “Matlab7 程式設計, 旗標出版股份有限公司, 台北,” 2006.
  26. [12] J. Tian, W. Yu, and S. Xie, “An ant colony optimization algorithm for image edge detection,” in Evolutionary Computation, 2008. CEC 2008.(IEEE World Congress on Computational Intelligence). IEEE Congress on, 2008, pp. 751-756.
  27. [14] Z. Yi, "Nonrigid Image Registration Using Physically Based Models," 2006.
  28. [17] 劉鴻明, 蔡孟達, and 張元翔, “應用於影像縮放技術之內插法評估研究,” Chung Hua Journal of Science and Engineering, vol. 3, no. 5, pp. 43-49, 2005.
  29. [19] B. Seibold, “A compact and fast Matlab code solving the incompressible Navier-Stokes equations on rectangular domains mit18086 navierstokes. m,” 2008.
  30. [21] G. E. Christensen, “Deformable shape models for anatomy,” Washington University Saint Louis, Mississippi, 1994.
  31. [23] M. Dorigo, V. Maniezzo, and A. Colorni, “Ant system: optimization by a colony of cooperating agents,” Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, vol. 26, no. 1, pp. 29-41, 1996.
  32. [24] M. Perretto, and H. S. Lopes, “Reconstruction of phylogenetic trees using the ant colony optimization paradigm,” Genetics and Molecular Research, vol. 4, no. 3, pp. 581-589, 2005.
  33. [28] 楊淑瑩, 模式識別與智能計算:Matlab的技術實現: 電子工業出版社, 2011.
  34. [33] R. M. Gray, Entropy and information theory: Springer Science & Business Media, 2011.
  35. [34] C.-L. Yeh, “SPECT 基於互資訊和內插 CT 下應用影像特徵做 CT 與腦部影像對位,” 臺北科技大學電腦與通訊研究所學位論文, pp. 1-81, 2005.