Building Surface Refinement Using Cluster of Repeated Local Features by Cross Ratio
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
Using grammars for pattern recognition in images: A systematic review
ACM Computing Surveys (CSUR)
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Object recognition and shape matching are important issues in the field of image processing. Extraction and application of skeleton of a shape is widely used in these fields. In this paper shape matching and retrieval is performed using one of the skeleton-based methods called "shock graphs". By modifying and optimizing this method, results have been improved significantly, especially in the presence of occlusion and missing parts. In this extension, branch points are added as key points to the shock graph and its grammar and consequently a new grammar is developed. Our experimental results due to the modifications and extensions are presented with different examples and tests, especially in the presence of occlusion and missing parts.