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Volume 31 #3

Contents

  1. Development of functional impairments in the lateral geniculate nucleus of di erent hemispheres following early monocular deprivation
  2. Eye optics and retinal topography in the Eurasian beaver Castor fiber L.
  3. Recognition of projectively transformed planar figures. X. Methods for finding an octet of invariant points of an oval contour – the result of introducing a developed theory into the schemes of oval description
  4. Mechanism of oxidative action of light on lipofuscin granules from the retinal pigment epithelium cells of the human eye: the role of superoxide radicals
  5. Spatial and temporal integration in the chain of the transduction of olfactory signals
  6. Adaptive image brightness stabilization for the industrial system of large moving object recognition
  7. Fast binary linear clustering algorithm for small dimensional histograms

Adaptive image brightness stabilization for the industrial system of large moving object recognition

© 2017 A. P. Gladkov, E. G. Kuznetsova, S. A. Gladilin, M. A. Gracheva

Institute for Information Transmission Problems RAS 127051 Moscow, Bolshoi Karetny per., 19

Received 03 Mar 2017

In this paper we investigate the task of developing algorithms for digital video camera sensitivity parameters control to adjust for scene brightness change caused by appearance and disappearance of large objects to be detected. We describe these controllable parameters (exposure, gain, DC-iris aperture) and the speci cs of adjusting them. We provide the experimental results of dependency between the obtained image brightness and the iris control signal value and propose a DC-iris control algorithm based on them. We introduce the algorithm to simultaneously control three sensitivity parameters for brightness adjustment and its modi cation for the case of large fast moving objects. A generalization of the algorithm is proposed to control the sensitivity parameters of a stereo-pair for the purpose aligning mean brightness of frames from both cameras.

Key words: camera sensitivity control, DC-iris, smart camera, brightness adaptation, autocalibration

Cite: Gladkov A. P., Kuznetsova E. G., Gladilin S. A., Gracheva M. A. Adaptivnaya stabilizatsiya yarkosti izobrazheniya v tekhnicheskoi sisteme raspoznavaniya krupnykh dvizhushchikhsya obektov [Adaptive image brightness stabilization for the industrial system of large moving object recognition]. Sensornye sistemy [Sensory systems]. 2017. V. 31(3). P. 247-260 (in Russian).

References:

  • Grigoryev A., Gladilin S., Khanipov T., Koptelov I., Bocharov D., Matsnev D. Architecture of a system for computer vision-based vehicle detection and classisication under natural conditions // Sensory systems. 2017. V. 31. No 1. P. 72–84 [in Russian]
  • Kravkov S. Glaz i ego rabota. M.: Medicina, 1932. 245 p. [in Russian]
  • Orlov V. Shema upravleniya diafragmoi po postoyannomu toku. 2007. URL: http://msevm.com/ md/703/02/sc.htm (accessed: 18.01.2017) [in Russian]
  • Shamshinova A., Volkov V. Functional methods of examination in ophthalmology. M.: Medicine, 1999. 416 p. [in Russian]
  • Birren J.E., Casperson R.C., Botwinick J. Age changes in pupil size // J. Gerontology. 1950. V. 5 (3). P. 216–221.
  • Cvetkovic S., Jellema H., de With N.H.P. Automatic level control for video cameras towards hdr techniques // EURASIP J. Image Video Process. 2010. ID 197194. P. 1–30.
  • Hamilton J.F., Compton J.T. Processing color and panchromatic pixels. U. S. Patent 0,024,879 A1, to Eastman Kodak Co., Patent and Trademark O ce, Washington D. C. Feb. 2007.
  • Howard I.P. Perceiving in depth, vol. 1: basic mechanisms. Oxford University Press. 2012, 664 p.
  • Hyden H., Wilhelmsson P. Automatic exposure control in network video cameras // MSc Theses. 2011. 57 p.
  • Khanipov T., Koptelov I., Grigoryev A., Kuznetsova E., Nikolaev D. Vision-based industrial automatic vehicle classi er // Proc. SPIE. 7th Int. Conf. Machine Vision. 2015. V. 9445, 944511. P. 1–5.
  • Lam B.L., Thompson H.S., Corbett J. J. The prevalence of simple anisocoria // Am.J. Ophthalmol. 1987. V. 104 (1). P. 69–73.
  • Lamb T. D. The role of photoreceptors in light-adaptation and dark-adapation of the visual system // Vision: Coding and effciency / Ed. Blakemore C. Cambridge Univ. Press, 1993. Ch. 15. P. 161–168.
  • Laurens H. Studies on the relative physiological value of spectral lights III. The pupillomotor effects of wave-lengths of equal energy content // Am. J. Physiol. 1923. V. 64. P. 97–119.
  • Nourani-Vatani N., Roberts J. M. Automatic camera exposure control // Proc. Australasian Conf. Robot. Automat. 2007. P. 1–6.
  • Reeves P. The response of the average pupil to various intensities of light // JOSA. 1920. V. 4 (2). P. 35–43.
  • Sirois S., Brisson J. Pupillometry // Wiley Interdisciplinary Reviews: Cognitive Science. 2014. V. 5 (6). P. 679–692.
  • Schlyter P. Radiometry and photometry in astronomy. 2009. URL: stjarnhimlen.se/comp/radfaq.html (accessed: 18.01.2017).
  • Visillect service LLC Automatic Vehicle Classi er – Visillect. URL: http://visillect.com/en/avc (accessed: 18.01.2017).
  • Winn B., Whitaker D., Elliott D.B., Phillips N.J. Factors affecting light-adapted pupil size in normal human subjects // Invest. Ophthalm. Vis. Sci. 1994. V. 35 (3). P. 1132–1137.