A Shape-Matching Technique Using Skeletal Graphs
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Abstract
A novel shape-matching algorithm using skeletal graphs in this paper. The topology of skeletal graphs is captured and compared at the node level. Such graph representation allows preservation of the skeletal graph’s coherence without scarifying the flexibility of matching similar portions of graphs across different levels. Using appropriate sampling resolution, the proposed approach is able to achieve a high recognition rate, and at the same time, significantly reduce space and time complexity of matching. This approach is tested against the Directed Acyclic Graph (DAG) method on noisy graphs and occluded or cluttered scenes. The results show that this approach is an effective and efficient technique for shape recognition.
Keywords: Skeletal graph, graph matching, shape recognition, shock graph
Corresponding author: E-mail: khnualsa@kmitl.ac.th
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