Affiliation:
1. Department of Computer Science, LRIA Laboratory, USTHB University, Algiers, Algeria
Abstract
The author presents in this paper a new approach for indexing and Content-based image retrieval based on the Quad-tree structure. The 3D objects are represented by their silhouettes and codified following the filling rate of each quadrant at different levels of the quad-tree subdivision. The author proposes a modified linear codification for silhouettes, this method improves the processing time because, in opposite to the traditional algorithms, the author’s algorithm has not a processing time that is proportional to the number of pixels in the image. As the same descriptor may characterize a set of different shapes, the author proposes also, efficient similarity measures to distinguish different objects having the same index in order to apply the approach to the retrieval process.
Subject
General Earth and Planetary Sciences,General Environmental Science
Reference43 articles.
1. Alvarado, C., Oltmans, M., & Davis, R. (2002). A framework for multi-domain sketch recognition. In Proceedings of AAAI Spring Symposium on Sketch Understanding.
2. Comparison of detailed descriptors of noisy silhouettes. Machine;S.Aouat;Graphics & Vision,2009
3. Coarse comparison of silhouettes using XLWDOS language.;S.Aouat;International Journal for Computational Vision and Biomechanics,2009
4. Aouat, S., & Larabi, S. (2010a). Indexing binary images using quad-tree decomposition. International Conference on System, Man, and Cybernetics, 10-13.
5. MATCHING DESCRIPTORS OF NOISY OUTLINE SHAPES