Graph-based shape indexing
Machine Vision and Applications, cilt.23, sa.3, ss.541-555, 2012 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 23 Sayı: 3
- Basım Tarihi: 2012
- Doi Numarası: 10.1007/s00138-010-0290-z
- Dergi Adı: Machine Vision and Applications
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Sayfa Sayıları: ss.541-555
- Anahtar Kelimeler: Information retrieval, Laplacian spectrum, Majorization, Matrix analysis, Shape indexing
- Ankara Yıldırım Beyazıt Üniversitesi Adresli: Hayır
Özet
Graphs have become growingly important in representing shapes in computer vision. Given a query graph, it is essential to retrieve similar database graphs efficiently from a large database. In this paper, we present a graph-based indexing technique which overcomes significant drawbacks of the previous work (Demirci et al. in Comput Vis Image Underst 110(3):312-325, 2008) using a recently developed theorem from the domain of matrix analysis. Our technique starts by representing the topological structure of a graph in a vector space. As done in the previous work, the topological structure of a graph is constructed using its Laplacian spectra. However, unlike the previous approach, which represents all sugraphs of a database graph in the vector space to account for local similarity, a database graph in the proposed framework is represented as a single vector. By performing a range search around the query, the proposed indexing technique returns a set with both partial and global similarity. Empirical evaluation of the algorithm on an extensive set of retrieval trials including a comparison with the previous approach in both 2D and 3D demonstrates the effectiveness, efficiency, and robustness of the overall approach. © Springer-Verlag 2012.