Sunday, October 16, 2005 4:48 AM

Jekky, Singapore

My current problem is given two data set (can be represented as string, tree, graph or any other pattern representation), how to efficient measure their approximate, inexact homology (isomorphism)?
I want the techniques that can find the matching with the following characteristics:
  • between different size of data set. Some points donot have correspondence;
  • approximate & inexact match; some points have not exact but approximate correspondence;
  • many-to-many correspondence instead of injective matching;
Only the matching score and scale information is required, can we design efficient algorithm to achieve these information? It's related to string, tree, point set, graph matching! The whole area of these problem is named as structural pattern recognition. It is also relatd to combinatoral optimization. But until now, I haven't found a good self-study material about these area.