Driver’s eye blinking detection using novel color and texture segmentation algorithms

Abstract

In this paper we propose a system that measures eye blinking rate and eye closure duration. The system consists of skin-color segmentation, facial features segmentation, iris positioning and blink detection. The proposed skin-segmentation procedure is based on a neural network approximation of a RGB skin-color histogram. This method is robust and adaptive to any skin-color training set. The largest remaining skin-color region among skin-color segmentation results is further segmented into open/closed eyes, lips, nose, eyebrows, and the remaining facial regions using a novel texture segmentation algorithm. The segmentation algorithm classifies pixels according to the highest probability among the estimated facial feature class probability density functions (PDFs). The segmented eye regions are analyzed with the Circular Hough transform with the purpose of finding iris candidates. The finial iris position is selected according to the location of the maximum correlation value obtained from correlation with a predefined mask. The positions of irises and eye states are monitored through time to estimate eye blinking frequency and eye closure duration. The method of the driver drowsiness detection using these parameters is illustrated. The proposed system is tested on CCD and CMOS cameras under different environmental conditions and the experimental results show high system performance.

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Correspondence to Jong-Soo Lee.

Additional information

Recommended by Editorial Board member Dong-Joong Kang under the direction of Editor Young-Hoon Joo.

This work was supported by the 2006 Research Fund of University of Ulsan.

Artem A. Lenskiy received his Master’s degree in Digital Signal Processing and Data Analysis in 2004 from the Novosibirsk State Technical University, Russia and a Ph.D. degree in EE from the University of Ulsan, Korea in 2010. He is currently lecturing at Korea University of Technology and Education (Koreatech), Korea. His research interests include computer vision problems and various applications of processes with long range dependence.

Jong-Soo Lee received his Bachelors degree in Electrical Engineering in 1973 from Seoul National University and his M.S. degree in 1981. In 1985 he was awarded his Ph.D. from Virginia Polytechnic Institute and State University, Blacksburg, USA. He is currently working in the area of multimedia at the University of Ulsan in Korea. His research interests include development of personal English cultural experience programs using multimedia and usability interface techniques to facilitate the acquisition of English language skills by Koreans. He is also working on vocal tract modeling from speech data based on fluid dynamics.

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Lenskiy, A.A., Lee, JS. Driver’s eye blinking detection using novel color and texture segmentation algorithms. Int. J. Control Autom. Syst. 10, 317–327 (2012). https://doi.org/10.1007/s12555-012-0212-0

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Keywords

  • Driver awareness control
  • facial features detection
  • iris detection and tracking
  • skin segmentation
  • texture segmentation