Investigation of Effectiveness of Simple Thresholding for Accurate Yawn Detection

  • Viswanath K. ReddyEmail author
  • K. S. Swathi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 553)


Drowsiness of a person is major cause for accidents and to avoid accidents alerting person at right time is very necessary. Yawning is one of the signs, which indicates whether the person is drowsy or not. Most of the algorithms in literature detect yawn state considering the region between the lips. Mouth localization is the fundamental step in yawn detection. Region between the lips is segmented using algorithms of different complexities. In this work, a simple segmentation algorithm like thresholding is investigated for its effectiveness. The segmented region with maximum area within the mouth region is considered to classify the frame as yawn frame or otherwise. Yawn video sequences from YawDD dataset are used to test and validate the algorithm. Yawn detection accuracy using the proposed algorithm is 76% which is bit higher than the accuracy obtained with more complex algorithm. Such simple algorithms might be more useful for real-time applications. The time consumption of the implementation is to be verified.


Driver drowsiness Face and eye detection Focused mouth region Image processing based Yawn detection 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.Faculty of Engineering and Technology, Department of ECEM. S. Ramaiah University of Applied SciencesBengaluruIndia
  2. 2.Digital Signal and Image ProcessingM. S. Ramaiah University of Applied SciencesBengaluruIndia

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