Title
Spectral shape descriptor using spherical harmonics
Abstract
In this paper, we propose a spectral descriptor for shapes of objects. The method relies on transforming the 2D objects into 3D space; distance transform and scale space theory is used to transform objects into 3D space. Spherical harmonics of the voxel grid are used to obtain shape descriptors. The proposed methods are compared against two existing methods which use spherical harmonics for shape based retrieval of images. Comparison is done based on ranking of images which is articulated in recall-precision curves. MPEG-7 Still Images Content Set is used for performing experiments. Experimental results show that the performance of the proposed descriptor is significantly better than other methods in the same category.
Year
DOI
Venue
2010
10.3233/ICA-2010-0335
Integrated Computer-Aided Engineering
Keywords
Field
DocType
recall-precision curve,proposed descriptor,spectral shape descriptor,existing method,spectral descriptor,shape descriptors,spherical harmonic,scale space theory,content set,feature extraction
Voxel,Computer vision,Pattern recognition,Ranking,Spherical harmonics,Scale space,Feature extraction,Distance transform,Artificial intelligence,Spectral shape analysis,Mathematics,Grid
Journal
Volume
Issue
ISSN
17
2
1069-2509
Citations 
PageRank 
References 
3
0.40
13
Authors
6
Name
Order
Citations
PageRank
Atul Sajjanhar115419.00
Guojun Lu2196582.04
Dengsheng Zhang32462100.00
Jingyu Hou418116.93
Wanlei Zhou52295189.31
Yi-ping Phoebe Chen61060128.42