Earticle

초록

영어

Hausdorff distance is a common image registration method that is based on the edge features in the image. Theoretically, using Hausdorff distance method, the rotation, scaling and translation factors of the image can be obtained by searching the four-dimensional space that includes one rotation factor, one scaling factor and two translation factors. However, each additional factor means that the dimension degree of searching space is increased one more. The searching speed will be greatly reduced with the increasing of dimension degree. This paper presents a new image registration algorithm that combines the Hausdorff distance with the angle transform. Using this method, the translation factors can be obtained by Hausdorff distance and the angle transform can be directly computed. There is three step for finishing the image registration through the new method. Firstly, discrete Canny edge detection is used on the image. Secondly, the linear features of the image is directly used to calculate the rotation angle parameter. Then Hausdorff distance is used searching in two-dimensional space for getting the translation parameters of the image. Simulation results verified the correctness and validity of the paper method.

목차

Abstract
 1. Introduction
 2. Feature Extraction
  2.1. Continuous Canny Method
  2.2. Discrete Canny Edge Extraction
 3. Image Registration
  3.1. Hausdorff Distance
  3.2. Translation Factors based on Hausdorff Distance
  3.3. Hausdorff Distance and Angle Calculation
 4. Simulation Result
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Liu Hui [ Department of Electrical and Information Engineering, Beijing University of Civil Engineering and Architecture ]
• Zhang Zhichun [ Department of Electrical and Information Engineering, Beijing University of Civil Engineering and Architecture ]
• Wei Dong [ Department of Electrical and Information Engineering, Beijing University of Civil Engineering and Architecture ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605