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Proceedings Paper

A fast tag searching method based on orientation code entropy and density
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Paper Abstract

This paper aims to propose a fast image searching method from environmental observation images even in the presence of scale changes. A new scheme has been proposed for extracting feature areas as tags based on a robust image registration algorithm called Orientation code matching. Extracted tags are stored as template images and utilized in tag searching. As the number of tags grows, the searching cost becomes a serious problem. Additionally, change in viewing positions cause scale change of an image and matching failure. In our scheme, richness in features is important for tag generation and the entropy is used to evaluate the diversity of edge directions which are stable to scale change of the image. This characteristic contributes to limitation of searching area and reduction in calculation costs. Scaling factors are estimated by orientation code density which means the percentage of effective codes in fixed size tag areas. An estimated scaling factor is applied to matching a scale of template images to one of observation images. Some experiments are performed in order to compare computation time and verify effectiveness of estimated scaling factor using real scenes.

Paper Details

Date Published: 6 December 2005
PDF: 12 pages
Proc. SPIE 6051, Optomechatronic Machine Vision, 605103 (6 December 2005); doi: 10.1117/12.645755
Show Author Affiliations
Hidenori Takauji, Hokkaido Univ. (Japan)
Shun'ichi Kaneko, Hokkaido Univ. (Japan)
Takayuki Tanaka, Hokkaido Univ. (Japan)


Published in SPIE Proceedings Vol. 6051:
Optomechatronic Machine Vision
Kazuhiko Sumi, Editor(s)

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