Quantitative measurements of feature indexing for 2D binary images of hexagonal grid for image retrieval

Zhi Jie Zheng; Clement H. C. Leung

doi:10.1117/12.205283

23 March 1995 Quantitative measurements of feature indexing for 2D binary images of hexagonal grid for image retrieval

Zhi Jie Zheng, Clement H. C. Leung

Proceedings Volume 2420, Storage and Retrieval for Image and Video Databases III; (1995) https://doi.org/10.1117/12.205283
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1995, San Jose, CA, United States

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.

Citation Download Citation

Zhi Jie Zheng and Clement H. C. Leung "Quantitative measurements of feature indexing for 2D binary images of hexagonal grid for image retrieval", Proc. SPIE 2420, Storage and Retrieval for Image and Video Databases III, (23 March 1995); https://doi.org/10.1117/12.205283

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