Improvement of Retrieval Speed and Required Amount of Memory for Geometric Hashing by Combining Local Invariants
Language
English
Type
Proceedings of International Conferences
Authors
Masakazu Iwamura, Tomohiro Nakai, Koichi Kise
Title
Improvement of Retrieval Speed and Required Amount of Memory for Geometric Hashing by Combining Local Invariants
Journal
Proc. 18th British Machine Vision Conference (BMVC2007)
Vol.
2
Pages
pp.1010-1019
Location
Warwick, UK
Reviewed
Reviewed
Date
September 2007
Research fields
Document Image Analysis, Document Image Retrieval
Key
Iwamura2007_BMVC (id=978)
Abstract
The geometric hashing (GH) is a well-known model-based object
recognition technique with good properties both
in retrieval speed and required amount of memory.
However, it has a significant weak point;
as the number of objects increases,
both retrieval speed and required amount of memory increase in
the cubic, fourth or higher order.
Recently, a new technique ``locally likely arrangement hashing (LLAH)''
whose computational cost is a linear order
has been proposed.
The objective of the current paper is to reveal how LLAH improves
the performance.
By comparing GH and LLAH,
we describe four primary factors of the performance improvement.
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