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Proceedings Article

Image retrieval based on multidimensional feature properties

[+] Author Affiliations
Yew H. Ang, Z. Li, Sim Heng Ong

National Univ. of Singapore (Singapore)

Proc. SPIE 2420, Storage and Retrieval for Image and Video Databases III, 47 (March 23, 1995); doi:10.1117/12.205317
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From Conference Volume 2420

  • Storage and Retrieval for Image and Video Databases III
  • Wayne Niblack; Ramesh C. Jain
  • San Jose, CA | February 05, 1995

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.

© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Citation

Yew H. Ang ; Z. Li and Sim Heng Ong
"Image retrieval based on multidimensional feature properties", Proc. SPIE 2420, Storage and Retrieval for Image and Video Databases III, 47 (March 23, 1995); doi:10.1117/12.205317; http://dx.doi.org/10.1117/12.205317


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