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Hedging Uncertainty in Rough Set-based Approach with Fuzzy Decision

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Author(s): Ning Chen | Bo-Qin Feng | Haixiao Wang | Hao Zhang

Journal: Information Technology Journal
ISSN 1812-5638

Volume: 4;
Issue: 4;
Start page: 387;
Date: 2005;
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Keywords: E-government | uncertainty | automatic authentication | rough set

ABSTRACT
This study introduced a technique for authenticating the vehicle engines by comparing the images of the imprints of the identification number acquired when the vehicle was first registered and the ones acquired from the routine yearly vehicle inspection. The images were taken by rubbing a pencil over a piece of paper covered over the images and then scanned into a computer as binary image. Due to the nature of the acquiring technique, the acquired images have lots of artifacts caused by the shape and the condition of the engine surface and unevenness of rubbing the pencils by hand. The rough set-based approach was used to handle uncertainty arisen from artifacts in the acquired images. But, it has been proved to be NP-hard to find all reductions and a minimal reduction and we generally use different heuristic algorithms to find a set of reductions. By an examination of prior knowledge, Gaussian distribution to describe uncertainty to achieve a minimal reduction was used. The approach can distinguish between two similar images on the basis of Inductive Logic Programming, as is superior to conventional pattern-recognition approach being merely capable of classifier. Furthermore, it can avoid some failures of the approach based on the correlation coefficient to authenticate binary image. The experiments show an accuracy rate close to 93.3%.
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