101. A Composite Descriptor for Shape Retrieval
- Author
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Guojun Lu, Atul Sajjanhar, Dengsheng Zhang, and Wanlei Zhou
- Subjects
business.industry ,Computer science ,InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL ,Search engine indexing ,Composite number ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Pattern recognition ,Set (abstract data type) ,Euclidean distance ,symbols.namesake ,Fourier transform ,Component (UML) ,Content (measure theory) ,symbols ,Computer vision ,Artificial intelligence ,business ,Image retrieval - Abstract
In this paper, a composite descriptor for shape retrieval has been proposed. The proposed descriptor is obtained from generic fourier descriptors (GFD) for the shape region and the shape contour. A composite descriptor derived from GFD of the shape region and the shape contour is used for indexing and retrieval of shapes. Difference between two images is computed as the Euclidean distance between their composite descriptors. Experiments are performed to test the effectiveness of the proposed descriptor for retrieval of 2d images. Sets of composite descriptors, obtained by assigning different weights to the region component and the contour component, are also evaluated. Item S8 within the MPEG-7 still images content set is used for performing experiments; this dataset consists of 3621 still images. Experimental results show that the proposed descriptor is effective.
- Published
- 2007
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