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A composite descriptor for shape retrieval

Sajjanhar, Atul, Lu, Guojun, Zhang, Dengsheng and Zhou, Wanlei 2007, A composite descriptor for shape retrieval, in 6th IEEE/ACIS International Conference on Computer and Information Science : (ICIS 2007) in conjunction with 1st IEEE/ACIS International Workshop on e-Activity (IWEA 2007) : proceedings : 11-13 July, 2007, Melbourne, Australia, IEEE Computer Society, Los Alamitos, Calif., pp. 795-800.

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Title A composite descriptor for shape retrieval
Author(s) Sajjanhar, Atul
Lu, Guojun
Zhang, Dengsheng
Zhou, Wanlei
Conference name International Conference on Computer and Information Science (6th : 2007 : Melbourne, Australia)
Conference location Melbourne, Australia
Conference dates 11-13 July 2007
Title of proceedings 6th IEEE/ACIS International Conference on Computer and Information Science : (ICIS 2007) in conjunction with 1st IEEE/ACIS International Workshop on e-Activity (IWEA 2007) : proceedings : 11-13 July, 2007, Melbourne, Australia
Editor(s) Lee, Roger
Chowdhury, Morshed U.
Ray, Sid
Lee, Thuy
Publication date 2007
Conference series International Conference on Computer and Information Science
Start page 795
End page 800
Publisher IEEE Computer Society
Place of publication Los Alamitos, Calif.
Summary 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.
Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
ISBN 0769528414
9780769528410
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2007, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30008043

Document type: Conference Paper
Collections: School of Engineering and Information Technology
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