Abstract
In this paper, we propose a robust and efficient representation scheme for shape retrieval, which is based on the normalized maximal disks used to represent the shape of an object. The maximal disks are extracted by means of a fast skeletonization technique with a pruning algorithm. The logarithm of the radii of the normalized maximal disks is used to construct a histogram to represent the shape. The retrieval performance of this maximal disk based histogram approach is compared to other methods, including moment invariants, Zernike moments, and curvature scale-space. Experimental results show that our proposed representation scheme outperforms the other methods under affine transformation and different noise levels.
| Original language | English |
|---|---|
| Pages (from-to) | 9-12 |
| Number of pages | 4 |
| Journal | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
| Volume | 3 |
| Publication status | Published - 25 Sept 2003 |
| Event | 2003 IEEE International Conference on Accoustics, Speech, and Signal Processing - Hong Kong, Hong Kong Duration: 6 Apr 2003 → 10 Apr 2003 |
Keywords
- Histogram distance
- Maximal disk
- Shape descriptor
- Shape retrieval
- Skeletonization
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering