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We present a unified framework for modeling and solving invariant point pattern matching problems. Invariant features are encoded as potentials in a probabilistic graphical model. By using a specific kind of graph topology, different types of invariant matching models can be implemented via tree-width selection. Models with tree-widths 1, 2, 3 and 4 implement translation, similarity, affine and protective...
The 'basis graph' approach to structural matching uses a fixed set of small (4 node) graphs to characterize local structure. We compute mapping probabilities by first finding the probability of a basis graph being an induced subgraph of the input graph. The similarity of these probabilities is used to compare nodes of the input graphs. The method permits common subgraphs to be identified without the...
This paper presents a method for lossless compression of Indian language textual images. The study is an extension of the previously developed pattern matching and substitution (PM&S)-based method for lossy compression of similar images. Here an efficient method for residue coding is proposed and its performance is compared with CCITT Gr-IV and JBIG. A set of 20 text images for two most popular...
This paper exploits the properties of the commute time for the purposes of graph matching. Our starting point is the random walk on the graph, which is determined by the heat-kernel of the graph and can be computed from the spectrum of the graph Laplacian. We characterise the random walk using the commute time between nodes, and show how this quantity may be computed from the Laplacian spectrum using...
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