A model based method for characterization and location of curved image features
- First Online:
This paper deals with the development of a parametric model based method to locate and characterize accurately important curved features such as ellipses and B-splines based curves. The method uses all the grey level information of the pixels contained within a window around the feature of interest and produces a complete parametric model that best approximates in a mean-square sense the observed grey level image intensities within the working area. Promising experimental results have been obtained on real data.
Unable to display preview. Download preview PDF.
- 1.R. Deriche. Fast Algorithms For Low-Level Vision. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(1):78–88, January 1990.Google Scholar
- 2.R. Deriche. Recursively Implementing the Gaussian and Its Derivatives. In Proc. Second International Conference On Image Processing, pages 263–267, Singapore, September 7–11 1992.Google Scholar
- 3.R. Deriche and T. Blaszka. Recovering and Characterizing Image Features Using An Efficient Model Based Approach. In Computer Vision And Pattern Recognition, pages 530–535, New-York, June 14–17 1993.Google Scholar
- 4.P. Lipson, A.L. Yuille, D. O'Keeffe, J. Cavanaugh, J. Taaffe, and D. Rosenthal. Deformable Templates for Feature Extraction from Medical Images. In O.D. Faugeras, editor, First European Conference on Computer Vision, pages 413–417, Antibes France, April 1990.Google Scholar