Extraction of Eye and Mouth Features for Drowsiness Face Detection Using Neural Network

Elis Fitrianingsih; Endang Setyati; Luqman Zaman

doi:10.22219/kinetik.v3i2.589

Issue

Vol 3, No 2, May-2018

Issue Published : Apr 16, 2018

Extraction of Eye and Mouth Features for Drowsiness Face Detection Using Neural Network

https://doi.org/10.22219/kinetik.v3i2.589

Elis Fitrianingsih

Sekolah Tinggi Teknik Surabaya

Endang Setyati

Sekolah Tinggi Teknik Surabaya

Luqman Zaman

Sekolah Tinggi Teknik Surabaya

Corresponding Author(s) : Elis Fitrianingsih

oyrasile1@gmail.com

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, Vol 3, No 2, May-2018
Article Published : Apr 16, 2018

Abstract

Facial feature extraction is the process of searching for features of facial components such as eyes, nose, mouth and other parts of human facial features. Facial feature extraction is essential for initializing processing techniques such as face tracking, facial expression recognition or face shape recognition. Among all facial features, eye area detection is important because of the detection and localization of the eye. The location of all other facial features can be identified. This study describes automated algorithms for feature extraction of eyes and mouth. The data takes form of video, then converted into a sequence of images through frame extraction process. From the sequence of images, feature extraction is based on the morphology of the eyes and mouth using Neural Network Backpropagation method. After feature extraction of the eye and mouth is completed, the result of the feature extraction will later be used to detect a person’s drowsiness, being useful for other research.

Keywords

Facial Feature Extraction Frame Extraction Neural Network Back-Propagation

Fitrianingsih, E., Setyati, E., & Zaman, L. (2018). Extraction of Eye and Mouth Features for Drowsiness Face Detection Using Neural Network. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 3(2), 103-112. https://doi.org/10.22219/kinetik.v3i2.589

Download Citation

References

S. R. Benedict and J. S. Kumar, “Geometric shaped facial feature extraction for face recognition,” IEEE Int. Conf. Adv. Comput. Appl. ICACA, Pp. 275–278, 2017.
S. Alexander, "Application Program on Face Recognition in Real Time Using Backpropagation and Wavelet Haar Methods," 2013.
D. Susantyo, "Feature Extraction for Face Recognition on Mongoloid Race Using Principal Component Analysis (PCA)," Pp. 1–9.
G. He and J. Gan, "A Method for Singular Value Feature Extraction of Face Image," Pp. 37–40, 2004.
S. N. Luthfie, "Implementation of Artificial Network Nerves Backpropagation on Face Recognition Application Using Various Distance Using MATLAB 7.0," 2007.
I. Hermawan, "Development of Face Recognition System Using Generalized Learning Vector Quantization (GLVQ)," Pp. 6–8, 2015.
Husdi, “Pengenalan Ekspresi wajah Pengguna Elearning Menggunakan Artificial Neural Network Dengan Fitur Ekstraksi Local Binary Pattern Dan Gray Level Co-Occurrence Matrix,” Jurnal Ilmiah ILKOM, Vol. 8, No. 3, Pp. 212–219, Desember 2016.
Z. Abidin, “Development of Facial Expression Recognition System Using Artificial Network Nerves Backpropaagation (A Case on MUG Database),” J. Mat. Murni dan Terap., Vol. 5, No. 1, Pp. 21–30, 2011.
S. Kusmaryanto, “Artificial Network Nerves Backpropagation for Face Recognition with Extraction Feature Based Histogram Method,” Vol. 8, No. 2, Pp. 193–198, 2014.
Y. D. Q. J. Ying, S. Jing, and Z. Wei, "The Monitoring Method of Driver’ s Fatigue Based on Neural Network," No. c, Pp. 3555–3559, 2007.

References

S. R. Benedict and J. S. Kumar, “Geometric shaped facial feature extraction for face recognition,” IEEE Int. Conf. Adv. Comput. Appl. ICACA, Pp. 275–278, 2017.

S. Alexander, "Application Program on Face Recognition in Real Time Using Backpropagation and Wavelet Haar Methods," 2013.

D. Susantyo, "Feature Extraction for Face Recognition on Mongoloid Race Using Principal Component Analysis (PCA)," Pp. 1–9.

G. He and J. Gan, "A Method for Singular Value Feature Extraction of Face Image," Pp. 37–40, 2004.

S. N. Luthfie, "Implementation of Artificial Network Nerves Backpropagation on Face Recognition Application Using Various Distance Using MATLAB 7.0," 2007.

I. Hermawan, "Development of Face Recognition System Using Generalized Learning Vector Quantization (GLVQ)," Pp. 6–8, 2015.

Husdi, “Pengenalan Ekspresi wajah Pengguna Elearning Menggunakan Artificial Neural Network Dengan Fitur Ekstraksi Local Binary Pattern Dan Gray Level Co-Occurrence Matrix,” Jurnal Ilmiah ILKOM, Vol. 8, No. 3, Pp. 212–219, Desember 2016.

Z. Abidin, “Development of Facial Expression Recognition System Using Artificial Network Nerves Backpropaagation (A Case on MUG Database),” J. Mat. Murni dan Terap., Vol. 5, No. 1, Pp. 21–30, 2011.

S. Kusmaryanto, “Artificial Network Nerves Backpropagation for Face Recognition with Extraction Feature Based Histogram Method,” Vol. 8, No. 2, Pp. 193–198, 2014.

Y. D. Q. J. Ying, S. Jing, and Z. Wei, "The Monitoring Method of Driver’ s Fatigue Based on Neural Network," No. c, Pp. 3555–3559, 2007.

Issue

Vol 3, No 2, May-2018

Extraction of Eye and Mouth Features for Drowsiness Face Detection Using Neural Network

Corresponding Author(s) : Elis Fitrianingsih

Abstract

Keywords

Download Citation

References

Downloads