Fast indexing for shape-based image retrieval based on similarity measures of spatial features
Document Type
Conference Proceeding
Publication Date
11-23-2005
Abstract
In this paper, a new method for shape-based image retrieval is presented. We first identify the dominant points of an object. Then, the geometric moment and perimeter (relative to a referenced dominant point) for each dominant point are computed. A synthetic spectrum plotted from the normalized geometric moments vs. normalized distances is obtained. The area covered by and the perimeter of the spectrum are computed. These two values are used as similarity measures for fast indexing in a shape-based image database. The fine-grained comparisons, based on cross-sectional area and perimeter distribution, are performed on the candidates to select the best matching category. Our method can satisfy necessary requirements of cognitively similarity measures from visual perception, such as rotation, scaling and shearing invariance.
Identifier
27744451441 (Scopus)
Publication Title
IEE Conference Publication
ISSN
05379989
First Page
39
Last Page
44
Issue
2005-10882
Recommended Citation
Wong, Wai Tak; Shih, Frank Y.; and Su, Te Feng, "Fast indexing for shape-based image retrieval based on similarity measures of spatial features" (2005). Faculty Publications. 19477.
https://digitalcommons.njit.edu/fac_pubs/19477
