In this thesis, we introduce a new shape descriptor and a graph based matching algorithm to detect a template shape in an image that contains a single object. The shape descriptor, Generalized Beam Angle Statistics, GBAS is obtained with the generalization of the boundary based shape descriptor, Beam Angle Statistics, BAS cite{BAS}. GBAS improves BAS so that it can compute the feature vector of a boundary point without the requirement of the parametric boundary representation. This way, it can be used in matching an individual edge pixel with a boundary point of template shape, even if it is not possible to extract the shape boundary in the image with the available techniques.
Given a template shape, the matching algorithm solves the correspondence problem between the sampled boundary points of the template and the edges of the query image, using the GBAS feature vectors and the spatial information of edges. The match graph represents the correspondence problem and the optimum path on this graph gives the solution of it. Optimum path is found using a polynomial time algorithm that is based on the dynamic programming approach.
In the experiments, we show that the proposed shape descriptor is very powerful and the matching algorithm is capable of detecting a template shape in edge detected images under a variety of transformations and noise.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/2/12605412/index.pdf |
| Date | 01 October 2004 |
| Creators | Tola, Omer Onder |
| Contributors | Yarman-vural, Fatos Tunay |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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