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CLC number: TP2; TP391.41
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Received: 2009-03-12
Revision Accepted: 2009-06-24
Crosschecked: 2010-01-05
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Automatic inspection of LED indicators on automobile meters based on a seeded region growing algorithm
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Hong ZHOU, Hai-er XU, Pei-qi HE, Zhi-bai SONG, Chen-ge GENG. Automatic inspection of LED indicators on automobile meters based on a seeded region growing algorithm[J]. Journal of Zhejiang University Science C, 2010, 11(3): 199-205.
@article{title="Automatic inspection of LED indicators on automobile meters based on a seeded region growing algorithm",
author="Hong ZHOU, Hai-er XU, Pei-qi HE, Zhi-bai SONG, Chen-ge GENG",
journal="Journal of Zhejiang University Science C",
volume="11",
number="3",
pages="199-205",
year="2010",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C0910144"
}
%0 Journal Article
%T Automatic inspection of LED indicators on automobile meters based on a seeded region growing algorithm
%A Hong ZHOU
%A Hai-er XU
%A Pei-qi HE
%A Zhi-bai SONG
%A Chen-ge GENG
%J Journal of Zhejiang University SCIENCE C
%V 11
%N 3
%P 199-205
%@ 1869-1951
%D 2010
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C0910144
TY - JOUR
T1 - Automatic inspection of LED indicators on automobile meters based on a seeded region growing algorithm
A1 - Hong ZHOU
A1 - Hai-er XU
A1 - Pei-qi HE
A1 - Zhi-bai SONG
A1 - Chen-ge GENG
J0 - Journal of Zhejiang University Science C
VL - 11
IS - 3
SP - 199
EP - 205
%@ 1869-1951
Y1 - 2010
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.C0910144
Abstract: light emitting diode (LED) indicators used on automobile meters are essential for safe driving and few errors can be tolerated. The current manual inspection approach can achieve only 95% accuracy rate in weeding out errors occurring in the production process. It is imperative to improve the accuracy of the inspection process to better achieve the goal of safe driving. This paper proposes an automatic inspection method for LED indicators for use on automobile meters. Firstly, red-green-blue (RGB) color images of LED indicators are acquired and converted into R, G, and B intensity images. A seeded region growing (SRG) algorithm, which selects seeds automatically based on Otsu’s method, is then used to extract the LED indicator regions. Finally, a region matching process based on the seed and three area parameters of each region is applied to inspect the LED indicators one by one to locate any errors. Experiments on standard automobile meters showed that the inspection accuracy rate of this method was up to 99.52% and the inspection speed was faster compared with the manual method. Thus, the new method shows good prospects for practical application.
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