Title :
Efficient methods for hypothesis verification paradigms
Author_Institution :
Erlangen-Nurnberg Univ., Germany
fDate :
30 Aug-3 Sep 1992
Abstract :
This paper describes efficient methods for verification and their integration in hypothesis verification algorithms suitable for image analysis. The problem of verifying hypotheses can often be reduced (with some restrictions) to the calculation of maximal weighted bipartite graph-matchings or to the calculation of maximal flows minimizing a cost function. These are in known graph theoretic problems and there exist some efficient algorithms for them. These algorithms are faster than graph-searching algorithms, such as A*, and need less memory capacity. Their complexity does not depend on the choice of rating functions or heuristic cost estimation. Experimental results of the integration of such methods and an A*-algorithm as a control-algorithm are included
Keywords :
image processing; pattern recognition; A*-algorithm; cost function; hypothesis verification paradigms; image analysis; maximal flows; maximal weighted bipartite graph-matchings; Bipartite graph; Cost function; Heuristic algorithms; Image analysis; Image segmentation; Machine vision; NP-complete problem; Polynomials; Tree graphs;
Conference_Titel :
Pattern Recognition, 1992. Vol.I. Conference A: Computer Vision and Applications, Proceedings., 11th IAPR International Conference on
Conference_Location :
The Hague
Print_ISBN :
0-8186-2910-X
DOI :
10.1109/ICPR.1992.201623