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Proceedings Paper

Quantitative measurements of feature indexing for 2D binary images of hexagonal grid for image retrieval
Author(s): Zhi Jie Zheng; Clement H. C. Leung
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Paper Abstract

A new feature indexing scheme for binary images is proposed. Using the structures of the conjugate classification of the hexagonal grid, ten intrinsically geometric invariant clusters are identified to partition a binary image into ten feature cluster images. The numbers of feature points in feature images are evaluated. Using the ten integers, a probability model is defined to generate quantitative measurements for feature indexing. This provides intrinsic feature indexing sets for rapid retrieval images based on their contents. Two vectors of twelve probability measurements are used to describe different images in varying sizes and sample pictures and their feature indices are illustrated.

Paper Details

Date Published: 23 March 1995
PDF: 9 pages
Proc. SPIE 2420, Storage and Retrieval for Image and Video Databases III, (23 March 1995); doi: 10.1117/12.205283
Show Author Affiliations
Zhi Jie Zheng, Victoria Univ. of Technology (Australia)
Clement H. C. Leung, Victoria Univ. of Technology (Australia)


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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