Advanced SearchSearch Tips
A Facial Feature Area Extraction Method for Improving Face Recognition Rate in Camera Image
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
A Facial Feature Area Extraction Method for Improving Face Recognition Rate in Camera Image
Kim, Seong-Hoon; Han, Gi-Tae;
  PDF(new window)
Face recognition is a technology to extract feature from a facial image, learn the features through various algorithms, and recognize a person by comparing the learned data with feature of a new facial image. Especially, in order to improve the rate of face recognition, face recognition requires various processing methods. In the training stage of face recognition, feature should be extracted from a facial image. As for the existing method of extracting facial feature, linear discriminant analysis (LDA) is being mainly used. The LDA method is to express a facial image with dots on the high-dimensional space, and extract facial feature to distinguish a person by analyzing the class information and the distribution of dots. As the position of a dot is determined by pixel values of a facial image on the high-dimensional space, if unnecessary areas or frequently changing areas are included on a facial image, incorrect facial feature could be extracted by LDA. Especially, if a camera image is used for face recognition, the size of a face could vary with the distance between the face and the camera, deteriorating the rate of face recognition. Thus, in order to solve this problem, this paper detected a facial area by using a camera, removed unnecessary areas using the facial feature area calculated via a Gabor filter, and normalized the size of the facial area. Facial feature were extracted through LDA using the normalized facial image and were learned through the artificial neural network for face recognition. As a result, it was possible to improve the rate of face recognition by approx. 13% compared to the existing face recognition method including unnecessary areas.
Face Recognition;Facial Feature Area;Gabor Filter;Linear Discriminant Analysis;Artificial Neural Network;
 Cited by
eu-Lisa, "Biometrics in Large-Scale IT," European Agency for the operational management of large-scale IT systems in the area of freedom, security and justice, 2015.

Ramadan Gad, Ayman El-Sayed, Nawal El-Fishawy, and M. Zorkany, "Multi-Biometric Systems: Astate of the Art Survey and Research Directions," International Journal of Advanced Computer Science and Applications (IJACSA), Vol.6, No.6, pp.128-138, 2015.

Won-Seok Chae, "Face Recognition Technology Trends," ETRI Contents Service Lab in Next Generation Contents Laboratory, 2013.

Ravi Subban and Savitha Soundararajan, "Face Recognition Techniques using PCA and LDA," Vol.9, No.10, Special, pp.335-340, 2015.

Hyun-Joon Moon and Sang-Hoon Kim, "Face Recognition : A Survey," Korea Information Processing Society, Vol.20, No.3, pp.14-21, 2013.

Asavari G. Joshi and A. S. Deshpande, "Review of Face Recognition Techniques," International Journal of Advanced Research in Computer Science and Software Engineering, Vol.5, No.1, pp.71-75. 2015.

Jamal Hussain Shah, Muhammad Sharif, Mudassar Raza, Marryam Murtaza, and Saeed-Ur-Rehman, "Robust Face Recognition Technique under Varying Illumination," Journal of Applied Research and Technology, Vol.13, pp.97-105, 2015. crossref(new window)

In-Jung Lee, "A Tracking Algorithm to Certain People Using Recognition of Face and Cloth Color and Motion Analysis with Moving Energy in CCTV," Korea Information Processing Society, Vol.15B, No.3, pp.197-204, 2008.

Dhiren Pandit and Jayesh Dhodiya, "PCA+LDA Method for Face Recognition Using Neural Network," International Journal of Innovative Science and Modern Engineering (IJISME), Vol.3, No.6, pp.6-11. 2015.

Alireza Tofighi, Nima Khairdoost, Amirhassan Monadjemi, and Kamal Jamshidi, "A Robust Face Recognition System in Image and Video," I. J. Image, Graphics and Signal Processing, Vol.6, No.8, pp.1-11, 2014.

Sargam Munjal and Rinku Dixit, "Face Recognition System using PCA and Artificial Neural Networks," International Journal of Emerging Engineering Research and Technology, Vol.2, No.4, pp.54-59. 2014.

Nilesh S. Wadhe, Sharad W. Mohod, and Nikkoo N. Khalsa, "An Overview - Aritificial Network Based Advanced Face and Non-Face Recognition," International Journal of Engineering Studies and Technical Approach, Vol.1, No.1, pp.1-10, 2015. crossref(new window)

Steven C Charpra and Raymond P Canale, "Numerical Methods for Engineers 6th Edition," 2010.

The Database of Faces [Internet],