- Title
- Connectivity-based shape descriptors
- Creator
- Sajjanhar, Atul; Lu, Guojun; Zhang, Dengsheng; Zhou, Wanle
- Date
- 2010
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/73655
- Identifier
- vital:7067
- Identifier
-
https://doi.org/10.2316/Journal.202.2010.1.202-2601
- Identifier
- ISSN:1206-212X
- Abstract
- In this paper, we propose a method for indexing and retrieval of images based on shapes of objects. The concept of connectivity is introduced. 3D models are used to represent 2D images. 2D images are decomposed a priori using connectivity which is followed by 3D model construction. 3D model descriptors are obtained for 3D models and used to represent the underlying 2D shapes. We have used spherical harmonics descriptors as the 3D model descriptors. Difference between two images is computed as the Euclidean distance between their descriptors. Experiments are performed to test the effectiveness of spherical harmonics for retrieval of 2D images. The proposed method is compared with methods based on principal components analysis (PCA) and generic Fourier descriptors (GFD). It is found that the proposed method is effective. Item S8 within the MPEG-7 still images content set is used for performing experiments.
- Relation
- International Journal of Computers and Applications Vol. 32, no. 1 (2010), p. 93-98
- Rights
- Copyright ACTA Press
- Rights
- This metadata is freely available under a CCO license
- Subject
- Shape representation; Image retrieval; Content-based image retrieval; Pattern recognition; 0805 Distributed Computing; 1702 Cognitive Science
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