Publication Details
Bart Truyen, Ioannis Pratikakis, Yang Xin, Jan Cornelis

Proceedings IWSSIP 1995, 2nd International Workshop on Image and Signal Processing, Theory, Methodology, Systems and Applications

Contribution To Book Anthology


Matching analogous contours is of central importance in computer vision. In this paper, a new hierarchical finite difference method to match analogous contours is presented. In deriving this method, we have been inspired by a method due to Duncan2, who proposed a scheme for matching two contours based on the minimisation of a quadratic fitting criterion. This criterion consists of a curvature dependent bending energy term and a smoothness term. The innovation of our work is in the incorporation of a new smoothness term in the fitting criterion. As a direct consequence, the computational complexity is reduced and the equation corresponding to the minimisation of the fitting criterion is attributed a simple interpretation. The solution method itself is based on a standard finite difference approach. To improve the convergence of the matching process, a new multi-smoothing scheme is proposed. Experimental validation is carried out on three medical applications: (i) Matching of left ventricular contours in successive images of a time sequence of spin echo cardiac magnetic resonance (MR) images, (ii) Matching of brain object contours in consecutive slices of a digital brain atlas, (iii) Matching of brain object contours in segmented MR images to the outlines of the corresponding brain objects in a digital anatomical atlas.