Title: Drunkenness detection using a CNN with adding Gaussian noise and blur in the thermal infrared images

Authors: Kha Tu Huynh; Huynh Phuong Thanh Nguyen

Addresses: School of Computer Science and Engineering, International University, Vietnam National University of Ho Chi Minh City, Block 6, Linh Trung Ward, Thu Duc City, Ho Chi Minh City, Vietnam ' School of Computer Science and Engineering, International University, Vietnam National University of Ho Chi Minh City, Block 6, Linh Trung Ward, Thu Duc City, Ho Chi Minh City, Vietnam

Abstract: Drunkenness is now often regarded as one of society's most serious issues. The majority of road accidents are caused by drunk driving. This paper proposes a methodology based on evaluating a facial thermal infrared image, adding noise and filters for augmentation, and determining intoxication using machine learning algorithms. In drunkenness detection, most research focus on using RGB image of facial expressions like eye sate, head position, or functional state indicators. Sometimes it is not trusty when attempting to predict on certain people who have certain facial feature patterns that the machine learning algorithm learned to be a factor of drunkenness. The combination of using the thermal infrared image with some noise and filter then predicting by optimised convolution neural network (CNN) model approach 93% on accuracy proves the efficiency as well as the feasibility of the proposed method.

Keywords: drunkenness detection; convolutional neural network; CNN; thermal infrared image; Gaussian noise; blur; machine learning; augmentation.

DOI: 10.1504/IJIIDS.2022.126512

International Journal of Intelligent Information and Database Systems, 2022 Vol.15 No.4, pp.398 - 419

Received: 03 Feb 2022
Accepted: 13 Mar 2022
Published online: 27 Oct 2022 *

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