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Proceedings Paper

Image retrieval based on multidimensional feature properties
Author(s): Yew Hock Ang; Z. Li; Sim Heng Ong
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Paper Abstract

In this paper, multidimensional feature measures of object shapes and feature blobs for retrieval of ceramic artifacts (e.g., plates, vases, and bowls) are proposed. These measures capture the various granularity of image features necessary for representation of complex image objects and their painted designs. Object shape is characterized by region compactness, boundary eccentricity, region moment, and region convexity. High detailed regions are characterized by blob properties such as total blob size, number of blobs, dispersion of blobs, and central moment of blobs. Each set of multiple feature measures jointly forms a 4- dimensional feature vector in a multidimensional feature space. Feature abstraction of complex image details is further improved by the computing feature measurements on sub-resolution images. This allows features of different perceptual scales to be isolated and efficiently abstracted. We have applied our method of image content analysis for retrieval of ceramic artifacts and have shown that multiresolution multidimensional feature measures can adequately retrieve images with high perceptual similarity.

Paper Details

Date Published: 23 March 1995
PDF: 11 pages
Proc. SPIE 2420, Storage and Retrieval for Image and Video Databases III, (23 March 1995); doi: 10.1117/12.205317
Show Author Affiliations
Yew Hock Ang, National Univ. of Singapore (Singapore)
Z. Li, National Univ. of Singapore (Singapore)
Sim Heng Ong, National Univ. of Singapore (Singapore)

Published in SPIE Proceedings Vol. 2420:
Storage and Retrieval for Image and Video Databases III
Wayne Niblack; Ramesh C. Jain, Editor(s)

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