The Investigation on Multimodal Biometric Recognition

被引:0
|
作者
Geng, Ai-Li [1 ]
Liu, Liyang [2 ]
机构
[1] GuangDong Pharmaceut Univ, Elect Commerce Dept, Guangzhou 510006, Guangdong, Peoples R China
[2] Jilin Univ, Coll Phys, Changchun 130012, Peoples R China
关键词
recognition systems; fingerprint and iris biometry; recognition rate; multimodal biometric systems;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Biometrics is used to identify individual in groups by their characteristics, such as fingerprint, face, iris, voice and behavioral characteristics like hand written signature and keystroke. Normally, a majority of biometrics recognition systems adopt methods by using unique feature to discriminate different individual from groups. But there is some forgery, subjective modifications like making up exiting as usual. A multimodal biometric recognition systemusing multiple biometrics to identify is proposed. In addition, it can support better Equal Error Rate (EER), False Acceptance Rate (FAR) and False Rejection Rate (FRR) by combining two or more physical or behavioral features. With lots of approached have been proposed, experts also pay much attention to the methods mentioned in recent years. The objective of this paper is to support a survey of multimodal biometric recognition system and approach using face, fingerprint recognition and enhanced iris characters that commonly used recently.
引用
收藏
页码:110 / 113
页数:4
相关论文
共 50 条
  • [1] Data hiding for multimodal biometric recognition
    Giannoula, A
    Hatzinakos, D
    [J]. 2004 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOL 2, PROCEEDINGS, 2004, : 165 - 168
  • [2] Cascaded multimodal biometric recognition framework
    Baig, Asim
    Bouridane, Ahmed
    Kurugollu, Fatih
    Albesher, Badr
    [J]. IET BIOMETRICS, 2014, 3 (01) : 16 - 28
  • [3] Multimodal Biometric Person Recognition by Feature Fusion
    Huang, Lin
    Yu, Chenxi
    Cao, Xinzhe
    [J]. 2018 5TH INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING (ICISCE 2018), 2018, : 1158 - 1162
  • [4] Multimodal Biometric Recognition System for Cloud Robots
    Tian, Shuqing
    Im, Sung Gyu
    Lee, Suk Gyu
    [J]. INTERNATIONAL JOURNAL OF SECURITY AND ITS APPLICATIONS, 2015, 9 (07): : 79 - 87
  • [5] Complex common vector for multimodal biometric recognition
    Wang, Z. F.
    Han, Q.
    Li, Q.
    Niu, X. M.
    Busch, C.
    [J]. ELECTRONICS LETTERS, 2009, 45 (10) : 495 - 496
  • [6] Person Verification Based on Multimodal Biometric Recognition
    Joseph, Annie Anak
    Lian, Alex Ng Ho
    Kipli, Kuryati
    Chin, Kho Lee
    Mat, Dayang Azra Awang
    Voon, Charlie Sia Chin
    Ngie, David Chua Sing
    Song, Ngu Sze
    [J]. PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY, 2022, 30 (01): : 161 - +
  • [7] Quality-Aware Multimodal Biometric Recognition
    Soleymani, Sobhan
    Dabouei, Ali
    Taherkhani, Fariborz
    Iranmanesh, Seyed Mehdi
    Dawson, Jeremy
    Nasrabadi, Nasser M.
    [J]. IEEE Transactions on Biometrics, Behavior, and Identity Science, 2022, 4 (01): : 97 - 116
  • [8] Multimodal Biometric Recognition using Iris & Fingerprint
    Bharadi, Vinayak Ashok
    Pandya, Bhavesh
    Nemade, Bhushan
    [J]. 2014 5TH INTERNATIONAL CONFERENCE CONFLUENCE THE NEXT GENERATION INFORMATION TECHNOLOGY SUMMIT (CONFLUENCE), 2014, : 697 - 702
  • [9] Speaker Recognition using Multimodal Biometric System
    Roy, Devashree
    Shukla, Anupam
    [J]. 2013 INTERNATIONAL CONFERENCE ORIENTAL COCOSDA HELD JOINTLY WITH 2013 CONFERENCE ON ASIAN SPOKEN LANGUAGE RESEARCH AND EVALUATION (O-COCOSDA/CASLRE), 2013,
  • [10] Complex kernel PCA for multimodal biometric recognition
    Wang, Zhifang
    Han, Qi
    Niu, Xiamu
    [J]. IEICE ELECTRONICS EXPRESS, 2009, 6 (16): : 1131 - 1136