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Applied Optics

Applied Optics


  • Vol. 51, Iss. 12 — Apr. 20, 2012
  • pp: 1865–1871

Design of an LED-based sensor system to distinguish human skin from workpieces in safety applications

Oliver Schwaneberg, Holger Steiner, Peter Haring Bolívar, and Norbert Jung  »View Author Affiliations

Applied Optics, Vol. 51, Issue 12, pp. 1865-1871 (2012)

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Commercial light curtains use a technique known as muting to differentiate between work pieces and other objects (e.g., human limbs) based on precise model knowledge of the process. At manually fed machinery (e.g., bench saws), such precise models cannot be derived due to the way the machinery is used. This paper presents a multispectral scanning sensor to classify an object’s surface material as a new approach for the problem. The system is meant to detect the presence of limbs and therefore optimized for human skin detection. Evaluation on a test set of skin and (wet) wood samples showed a sufficiently high reliability with respect to safety standards.

© 2012 Optical Society of America

OCIS Codes
(120.0280) Instrumentation, measurement, and metrology : Remote sensing and sensors
(120.1880) Instrumentation, measurement, and metrology : Detection
(120.3940) Instrumentation, measurement, and metrology : Metrology
(120.4570) Instrumentation, measurement, and metrology : Optical design of instruments
(280.4788) Remote sensing and sensors : Optical sensing and sensors

ToC Category:
Instrumentation, Measurement, and Metrology

Original Manuscript: September 28, 2011
Revised Manuscript: January 2, 2012
Manuscript Accepted: February 3, 2012
Published: April 11, 2012

Virtual Issues
Vol. 7, Iss. 6 Virtual Journal for Biomedical Optics

Oliver Schwaneberg, Holger Steiner, Peter Haring Bolívar, and Norbert Jung, "Design of an LED-based sensor system to distinguish human skin from workpieces in safety applications," Appl. Opt. 51, 1865-1871 (2012)

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  1. D. Reinert, O. Schwaneberg, N. Jung, S. Ullmann, W. Olbert, D. Kamin, and R. Kohler, “Finger and hand protection on circular table and panel saws,” Saf. Sci. 47, 1175–1184 (2009). [CrossRef]
  2. O. Schwaneberg, U. Köckemann, H. Steiner, and N. Jung, “A Near-Infrared LED-based Material Classification Sensor System,” in Optical Sensors, OSA Technical Digest (CD) (Optical Society of America, 2011), paper SMD4.
  3. J. A. Jacquez, J. Huss, W. McKeehan, J. M. Dimitroff, and H. F. Kuppenheim, “Spectral Reflectance of Human Skin in the Region 0.7–2.6 μm,” J. Appl. Physiol. 8, 297 (1955).
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  5. A. S. Nunez and M. J. Mendenhall, “Detection of Human Skin in Near Infrared Hyperspectral Imagery,” in Proceedings of IEEE Symposium on Geoscience and Remote Sensing (IGARSS, 2008), vol. 2, pp. 621–624.
  6. M. Stoerring, “Computer Vision and Human Skin Colour,” PhD thesis (Aalborg University, 2004).
  7. D. Reinert, N. Jung, and O. Schwaneberg, “A manually fed machine for working on materials, objects and the like, and protective means for such a machine,” European patent EP2054193/EP2193878 (6May2009).
  8. K. H. Yang and J. D. Kingsley, “Calculation of coupling losses between light emitting diodes and low-loss optical fibers,” Appl. Opt. 14, 288–293 (1975). [CrossRef]
  9. D. J. Schroeder, “Signal-to-noise ratio,” in Astronomical Optics, (Academic, 1999), pp. 433–438.

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