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A novel algorithmic approach of open eye analysis for drowsiness detection

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Abstract

Drowsiness is the crucial reason for road accidents nowadays, as per the available statistics. Several valuable lives may collapse because of this. Such valuable lives can be rescued via the detection of drowsiness at its earlier stage. This paper emphasizes a novel algorithmic approach to recognize the driver’s drowsiness at its initial stage with remarkable accuracy via employing computer vision techniques purely. Our proposed work has selected the most noteworthy temporal features of eyes (Eye Aspect Ratio, pupil’s center) and head (tip of the nose) to classify the driver’s drowsy state more precisely. Further, our developed framework resolved the issue of occluded frames at its pre-processing step via applying the condition of occlusion. Afterward, we have imposed three checks via employing eye aspect ratio, pupil’s center, and head (tip of the nose) movement to ensure the correct drowsy state of the driver. Consequently, the performance and accuracy of the overall system have improved in contrast to existing Techniques. Thus, our proposed system has achieved an accuracy of 94.2% in open eye detection.

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Authors and Affiliations

  1. Computer Science and Engineering, National Institute of Technology Silchar, Silchar, Assam, 788010, India

    Nageshwar Nath Pandey & Naresh Babu Muppalaneni

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  1. Nageshwar Nath Pandey
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  2. Naresh Babu Muppalaneni
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Correspondence to Nageshwar Nath Pandey.

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Pandey, N.N., Muppalaneni, N.B. A novel algorithmic approach of open eye analysis for drowsiness detection. Int. j. inf. tecnol. 13, 2199–2208 (2021). https://doi.org/10.1007/s41870-021-00811-x

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