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2015 | 128 | 2B | B-474-B-476
Article title

Stable Light Level Detection in the Light Pools Using Neural Network Algorithms

Content
Title variants
Languages of publication
EN
Abstracts
EN
One of the requirements in machine vision applications is that the light source and the environment are selected correctly. If the analyzed object is not properly illuminated, it is inadequate for obtaining the desired result using the captured images. A correct lighting luminaire allows to distinguish the examined object from the environment it interacts with and ensures that its attributes are obtained correctly. In this study an intelligent dynamic lighting system for illumination of a closed area has been developed. The tested luminaire has three arms. Accelerometer readings are used for positioning and orientation. Using the developed system, the positions of the armature can be estimated by bipolar sigmoid technique, according to the point the user wants to illuminate. The system measures the light level with 72 LDR, calibrated with a luxmetre.
Keywords
EN
Year
Volume
128
Issue
2B
Pages
B-474-B-476
Physical description
Dates
published
2015-8
References
  • [1] M.S. Rea, The IESNA Lighting handbook: Reference & Application, 9th ed., IESNA, Illuminating Engineering Society Press, New York 2000
  • [2] J. Mitéran, P. Geveaux, R. Bailly, P. Gorria, Industrial Electronics, 7-11 July (1997)
  • [3] Zou Huadong, Zhu Liangrong, Tan Ming, 2009 Asia Pacific Conference on Postgraduate Research in Microelectronics & Electronics (PrimeAsia), Shanghai 2009, p. 392
  • [4] A. Hornberg, Handbook of Machine Vision, 1st ed., Wiley-VCH, Weinheim 2008
  • [5] A. Arısoy,, M.Sc. Thesis, Süleyman Demirel University Graduate School of Applied and Natural Sciences, Isparta 2013
  • [6] M.Ş. Sözen, II. Ulusal Aydınlatma Sempozyumu, Diyarbakır 2003, p. 1
  • [7] B. Büyükarıkan, M.Sc. Thesis, Süleyman Demirel University Graduate School of Applied and Natural Sciences, Isparta 2014
  • [8] A.W. Louw, C. Neethling, Proc. 21st Domestic Use of Energy Conference (DUE), Cape Town 2013
Document Type
Publication order reference
YADDA identifier
bwmeta1.element.bwnjournal-article-appv128n2b145kz
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