Numerical Simulation and Design of Machine Learning Based Real Time Fatigue Detection System
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Abstract
The proposed research is a step to implement real time image segmentation and drowsiness with help of machine learning methodologies. Image segmentation has been implemented in real time in which the segments of mouth and eyes have been segmented using image processing. Input can be provided by the help of real time image acquisition system such as webcam or internet of things based camera. From the video input, image frames has been extracted and processed to obtain real time features and using clustering algorithms segmentation has been achieved in real time. In the proposed work a Support Vector Machine (SVM) based machine learning method has been implemented emotion detection using facial expressions. The algorithm has been tested under variable luminance conditions and performed well with optimum accuracy as compared to contemporary research.
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References
Gibert, Xavier, Vishal M. Patel, Demetrio Labate, and Rama Chellappa. "Discrete shearlet transform on GPU with applications in anomaly detection and denoising." EURASIP Journal on Advances in Signal Processing 2014, no. 1 (2014): 64.
Li, G., Lee, B. L. & Chung, W. Y., “Smartwatch- Based Wearable EEG System for Driver Drowsiness Detection”, Sensors Journal, IEEE, vol.- 15, no.-12, pp. 7169-7180, 2015.
Zhang, D. D., Li, X. & Liu, Z., “Data management and Internet computing for image/pattern analysis”, Springer Science & Business Media, vol.-11, 2012.
Li, P., Liu, X., Xiao, L. & Song, Q., “Robust and accurate iris segmentation in very noisy iris images”, Image and vision computing, vol.-28, no.-2, pp. 246-253, 2012.
Yang, J.-P. . “A Novel Storage Virtualization Scheme for Network Storage Systems”. International Journal on Recent and Innovation Trends in Computing and Communication, vol. 10, no. 1, Jan. 2022, pp. 08-13, doi:10.17762/ijritcc.v10i1.5514.
Garcia, I., Bronte, S., Bergasa, L. M., Almazán, J. & Yebes, J., “Vision-based drowsiness detector for real driving conditions”, IEEE Intelligent Vehicles Symposium, pp. 618-623, June 2012.
Zhang, Z., & Zhang, J., “A strong tracking nonlinear robust filter for eye tracking”, Journal of control theory and applications, vol.-8(4), pp. 503-508, 2010.
Flores, M. J., Armingol, J. M., & de la Escalera A., “Real-time warning system for driver drowsiness detection using visual information”, Journal of Intelligent & Robotic Systems, vol.-59(2), pp. 103-125, 2010.
Tawari, Ashish, Kuo Hao Chen and Mohan Manubhai Trivedi, "Where is the driver looking: Analysis of head, eye and iris for robust gaze zone estimation", IEEE 17th International Conference on Intelligent Transportation Systems (ITSC), 2014.
Sudhakar, C. V., & Reddy, G. U. . (2022). Land use Land cover change Assessment at Cement Industrial area using Landsat data-hybrid classification in part of YSR Kadapa District, Andhra Pradesh, India. International Journal of Intelligent Systems and Applications in Engineering, 10(1), 75–86. https://doi.org/10.18201/ijisae.2022.270
Singh, R. K., et al., "A real-time heart-rate monitor using non-contact electrocardiogram for automotive drivers.", IEEE First International Conference on Control, Measurement and Instrumentation (CMI), 2016.
Blum, J., & Eskandarian, A., “Enhancing intelligent agent collaboration for flow optimization of railroad traffic”, Transportation Research Part A: Policy and Practice, vol.-36(10), pp. 919-930, 2012.
Basilio, Jorge Alberto Marcial, et al, "Explicit image detection using YCbCr space color model as skin detection", Proceedings of the 2011 American conference on applied mathematics and the 5th WSEAS international conference on Computer engineering and applications, IEEE ICCE, 2011.
R. F. Olanrewaju, O. O. Khalifa, A.-H. Hashim, A. M. Zeki, and A. A. Aburas, "Forgery Detection in Medical Images Using Complex Valued Neural Network (CVNN)", Australian Journal of Basic and Applied Sciences, 2011.
Feng, R., Zhang, G., & Cheng, B., “An on-board system for detecting driver drowsiness based on multi-sensor data fusion using Dempster-Shafer theory”, IEEE International Conference on Networking, Sensing and Control, pp. 897-902, March 2009.
Zhao, C. H., Zhang, B. L., Zhang, X. Z., Zhao, S. Q., & Li, H. X., “Recognition of driving postures by combined features and random subspace ensemble of multilayer perceptron classifiers”, Neural Computing and Applications, vol.-22(1), pp.-175-184, 2013.
Asthana, A., Marks, T. K., Jones, M. J., Tieu, K. H., & Rohith, M. V., “Fully automatic pose-invariant face recognition via 3D pose normalization”, International Conference on Computer Vision, pp. 937-944, Nov 2011.
Lichtenauer, J., Shen, J., Valstar, M., & Pantic, M., “Cost-effective solution to synchronised audio-visual data capture using multiple sensors”, Image and Vision Computing, vol.-29(10), pp. 666-680, 2011.
Sivaraman, S., & Trivedi, M. M., “Looking at vehicles on the road: A survey of vision-based vehicle detection, tracking, and behavior analysis”, IEEE Transactions on Intelligent Transportation Systems, vol.-14(4), pp. 1773-1795, 2013.
Smith, R. P., Shah, M., & da Vitoria Lobo, N. (2005), U.S. Patent No. 6,927,694. Washington DC, U.S. Patent and Trademark Office, 2005.
Saradadevi, Mandalapu, and Preeti Bajaj, "Driver fatigue detection using mouth and yawning analysis", International journal of Computer science and network security, no. 6, pp. 183-188, 2008.
Tan, Xiaoyang, Yi Li, Jun Liu, and Lin Jiang, "Face liveness detection from a single image with sparse low rank bilinear discriminative model", Springer, Berlin, Heidelberg European Conference on Computer Vision, pp. 504-517, 2010.
Wu, Yu-Shan, Ting-Wei Lee, Quen-Zong Wu, and Heng-Sung Liu, "An eye state recognition method for drowsiness detection", IEEE 71st Vehicular Technology Conference, pp. 1-5, 2010.
Tian, Zhichao, and Huabiao Qin. "Real-time driver's eye state detection." In IEEE International Conference on Vehicular Electronics and Safety, 2005., pp. 285-289. IEEE, 2005.
Sally Fouad Shady. (2021). Approaches to Teaching a Biomaterials Laboratory Course Online. Journal of Online Engineering Education, 12(1), 01–05. Retrieved from http://onlineengineeringeducation.com/index.php/joee/article/view/43
Li, Nan, Hong Huo, Yu-ming Zhao, Xi Chen, and Tao Hong, "A spatial clustering method with edge weighting for image segmentation", IEEE Geoscience and Remote Sensing Letters 10, no. 5, pp. 1124-1128, 2013.
Qin, Huabiao, Jun Liu, and Tianyi Hong, "An eye state identification method based on the Embedded Hidden Markov Model", IEEE International Conference on Vehicular Electronics and Safety (ICVES 2012), pp. 255-260, 2012.
Wang, Chi-Chen Raxle, and Jenn-Jier James Lien, "Automatic vehicle detection using local features--a statistical approach", IEEE Transactions on Intelligent Transportation Systems 9, no. 1, pp. 83-96, 2008.
Lenskiy, Artem A., and Jong-Soo Lee.,"Driver’s eye blinking detection using novel color and texture segmentation algorithms", International journal of control, automation and systems 10, no. 2, pp. 317-327, 2012.
Komarov, Alexander S., and Mark Buehner. "Adaptive probability thresholding in automated ice and open water detection from RADARSAT-2 images." IEEE Geoscience and Remote Sensing Letters 15, no. 4 (2018): 552-556.
Hu, S., Zheng, G., & Peters, B., “Driver fatigue detection from electroencephalogram spectrum after electrooculography artefact removal”, IET Intelligent Transport Systems, vol.-7(1), pp. 105-113, 2013.
Bai, Enjian, Yiyu Yang, and Xueqin Jiang. "Image digital watermarking based on a novel clock-controlled generator." In 2017 4th International Conference on Systems and Informatics (ICSAI), pp. 1224-1228. IEEE, 2017.
Evsutin, Oleg, Roman Meshcheryakov, Viktor Genrikh, Denis Nekrasov, and Nikolai Yugov. "An improved algorithm of digital watermarking based on wavelet transform using learning automata." In 2017 Second Russia and Pacific Conference on Computer Technology and Applications (RPC), pp. 49-53. IEEE, 2017.
Dogiwal, Sanwta Ram, Y. S. Shishodia, Abhay Upadhyaya, Hanuman Ram, and Satish Kumar Alaria. "Image Preprocessing Methods in Image Recognition." International Journal of Computers and Distributed Systems 1, no. 3 (2012): 96-99.
D. K. S. K. A., “A New Palm Print Recognition Approach by Using PCA & Gabor Filter”, ijfrcsce, vol. 4, no. 4, pp. 38–45, Apr. 2018.
S. K. Alaria, A. . Raj, V. Sharma, and V. Kumar, “Simulation and Analysis of Hand Gesture Recognition for Indian Sign Language using CNN”, IJRITCC, vol. 10, no. 4, pp. 10–14, Apr. 2022.