Attributed relational graph matching based on the nested assignment structure

• Published in: Pattern recognition Vol. 43; no. 3; pp. 914 - 928
• Main Authors: Kim, Duck Hoon, Yun, Il Dong, Lee, Sang Uk
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.03.2010; Elsevier
• Subjects: Applied sciences; ARG matching; Assignment; Attributed relational graph (ARG); Computer science; control theory; systems; Exact sciences and technology; Information systems. Data bases; Information theory; Information, signal and communications theory; Memory organisation. Data processing; Nested assignment structure; Relation vector space; Software; Telecommunications and information theory; Assignment; Relation vector space; ARG matching; Attributed relational graph (ARG); Nested assignment structure; Performance evaluation; Similarity; Updating; Iterative method; Algorithm; Combinatorial method; Vector space; Information processing; Matching task; Graph matching
• ISSN: 0031-3203; 1873-5142
• DOI: 10.1016/j.patcog.2009.09.012

In this paper, we propose a new ARG matching scheme based on the nested assignment structure to assess the similarity between two attributed relational graphs (ARGs). ARGs are represented by nodes and edges containing unary attributes and binary relations between nodes, respectively. The nested assignment structure consists of inner and outer steps. In the inner step, to form a distance matrix, combinatorial differences between every pair of nodes in two ARGs are computed by using an assignment algorithm. Then, in the outer step, a correspondence between nodes in the two ARGs is established by using an assignment algorithm based on the distance matrix. The proposed ARG matching scheme consists of three procedures as follows: first, in the initializing procedure, the nested assignment structure is performed to generate an initial correspondence between nodes in two ARGs. Next, the correspondence is refined by iteratively performing the updating procedure, which also utilizes the nested assignment structure, until the correspondence does not change. Finally, the verifying procedure can be performed in case that some nodes to be matched in the two ARGs are missing. From experimental results, the proposed ARG matching scheme shows superior matching performance and localizes target objects robustly and correctly even in severely noisy and occluded scenes.