Face recognition using separate layers of the RGB image

被引:1
|
作者
Bours, Patrick
Helkala, Kirsi
机构
来源
2008 FOURTH INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATION HIDING AND MULTIMEDIA SIGNAL PROCESSING, PROCEEDINGS | 2008年
关键词
D O I
10.1109/IIH-MSP.2008.162
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In many cases face recognition of still images is performed with greyscale images. These images are actually converted from a color image to greyscale before the analysis takes place. A consequence of such a conversion is obviously loss of information, which could influence the performance of the face recognition system. It would be interesting to see if using one of the three color layers of the RGB image could give better recognition performance compared to the greyscale converted image. We conducted two experiments and the results indeed support this idea. We found that the red layer of the RGB image gives the best recognition performance, especially in the cases where an extra light source is used to light up (part of) the face of the participants in the experiments. In the case that the participants were facing the camera we saw the Equal Error Rate drop from 3.3% for the greyscale images to 1.8% for the red layer of the RGB images in our initial experiment.
引用
收藏
页码:1035 / 1042
页数:8
相关论文
共 50 条
  • [31] Range image invariant face recognition using wavelet transform
    Pansang, S
    Attachoo, B
    Kimpan, C
    Phokharatkul, P
    7TH WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL X, PROCEEDINGS: SIGNALS PROCESSING AND OPTICAL SYSTEMS, TECHNOLOGIES AND APPLICATIONS, 2003, : 156 - 160
  • [32] Face recognition in unrestricted posture using invariant image information
    Yutaka, S
    Yamaguchi, J
    MACHINE VISION AND ITS OPTOMECHATRONIC APPLICATIONS, 2004, 5603 : 21 - 30
  • [33] Face Spoof Attack Recognition Using Discriminative Image Patches
    Akhtar, Zahid
    Foresti, Gian Luca
    JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING, 2016, 2016
  • [34] A new distance criterion for face recognition using image sets
    Chin, TJ
    Suter, D
    COMPUTER VISION - ACCV 2006, PT I, 2006, 3851 : 549 - 558
  • [35] Face recognition using non-linear image reconstruction
    Duffner, S.
    Garcia, C.
    2007 IEEE CONFERENCE ON ADVANCED VIDEO AND SIGNAL BASED SURVEILLANCE, 2007, : 459 - 464
  • [36] Illumination compensation for face recognition using only one image
    Lin, Lan
    Zhao, Ge
    Tang, Yan-Dong
    Tian, Jian-Dong
    He, Si-Yuan
    Zidonghua Xuebao/Acta Automatica Sinica, 2013, 39 (12): : 2090 - 2099
  • [37] Face recognition with image sets using manifold density divergence
    Arandjelovic, O
    Shakhnarovich, G
    Fisher, J
    Cipolla, R
    Darrell, T
    2005 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOL 1, PROCEEDINGS, 2005, : 581 - 588
  • [38] Face Recognition on a Smart Image Sensor Using Local Gradients
    Valenzuela, Wladimir
    Soto, Javier E.
    Zarkesh-Ha, Payman
    Figueroa, Miguel
    SENSORS, 2021, 21 (09)
  • [39] RGB-D Face Recognition With Texture and Attribute Features
    Goswami, Gaurav
    Vatsa, Mayank
    Singh, Richa
    IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2014, 9 (10) : 1629 - 1640
  • [40] Infrared Polarized Face Recognition Based on RGB Color Space
    Wang Fangbin
    Jin Xu
    Zhu Darong
    Hu Ziliang
    Tang Sheng
    Lei Jingfa
    LASER & OPTOELECTRONICS PROGRESS, 2022, 59 (12)