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Irniger, C. and Bunke, H. (2003) Theoretical Analysis and Experimental Comparison of Graph Matching Algorithms for Database Filtering. Proceedings of 4th IAPR International Workshop on Graph Based Representations in Pattern Recognition, Vol. 2726, 30 June-2 July 2003, 118-129.
https://doi.org/10.1007/3-540-45028-9_11

has been cited by the following article:

• TITLE: Graph Based Filtering and Matching for Symbol Recognition

  AUTHORS: Vaishali Pawar, Mukesh Zaveri

  KEYWORDS: Graphs, Pattern Recognition, Information Retrieval, Graph Matching, Data Mining

  JOURNAL NAME: Journal of Signal and Information Processing, Vol.9 No.3, August 9, 2018

  ABSTRACT: Pattern recognition is a task of searching particular patterns or features in the given input. The data mining, computer networks, genetic engineering, chemical structure analysis, web services etc. are few rapidly growing applications where pattern recognition has been used. Graphs are very powerful model applied in various areas of computer science and engineering. This paper proposes a graph based algorithm for performing the graphical symbol recognition. In the proposed approach, a graph based filtering prior to the matching is performed which significantly reduces the computational complexity. The proposed algorithm is evaluated using a large number of input drawings and the simulation results show that the proposed algorithm outperforms the existing algorithms.