An Alternative to Graph Matching for Locating Objects from their Salient Features
Author(s) -
E.R. Davies
Publication year - 1988
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5244/c.2.43
Subject(s) - computer science , salient , matching (statistics) , graph , artificial intelligence , theoretical computer science , mathematics , statistics
means for locating objects in two dimensions. However, the technique has certain problems, since the maximal clique approach to graph matching which it employs can be excessively computation intensive. This raises the question of whether better results could be obtained by other means. Here we attempt to answer this question, and in particular to compare the LFF and GHT schemas. The actual comparison is carried out in section 4, sections 2 and 3 being devoted to respective preliminary studies of the two methods. The local-feature-focus method has become a standard means for robustly locating objects in two dimensions. Yet it is not without its difficulties, since the maximal clique approach to graph matching which it employs is excessively computation intensive, belonging to the class of NP-complete problems. Here we explore whether similar results can be obtained using other approaches, and in particular with the generalised Hough transform. The latter approach is found to be essentially equivalent to graph matching, while permitting objects to be located in polynomial (0(n )) time.
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