Beyond objective performance evaluation in multimodal biometric systems

2007 ◽  
Vol 62 (1-2) ◽  
pp. 156-176
Author(s):  
Doroteo T. Toledano ◽  
Álvaro Hernández Trapote ◽  
David Díaz Pardo de Vera ◽  
Rubén Fernández Pozo ◽  
Luis Hernández Gómez
2010 ◽  
Vol 43 (5) ◽  
pp. 1789-1800 ◽  
Author(s):  
Mingxing He ◽  
Shi-Jinn Horng ◽  
Pingzhi Fan ◽  
Ray-Shine Run ◽  
Rong-Jian Chen ◽  
...  

2021 ◽  
Author(s):  
Mohamed Abdul-Al ◽  
George Kumi Kyeremeh ◽  
Naser Ojaroudi Parchin ◽  
Raed A Abd-Alhameed ◽  
Rami Qahwaji ◽  
...  

Author(s):  
K Sasidhar ◽  
Vijaya L Kakulapati ◽  
Kolikipogu Ramakrishna ◽  
K KailasaRao

Author(s):  
Shashidhara H. R. ◽  
Siddesh G. K.

Authenticating the identity of an individual has become an important aspect of many organizations. The reasons being to secure authentication process, to perform automated attendance, or to provide bill payments. This need of providing automated authentication has led to concerns in the security and robustness of such biometric systems. Currently, many biometric systems that are organizations are unimodal, which means that use single physical trait to perform authentication. But, these unimodal systems suffer from many drawbacks. These drawbacks can be overcome by designing multimodal systems which use multiple physical traits to perform authentication. They increase reliability and robustness of the systems. In this chapter, analysis and comparison of multimodal biometric systems is proposed for three physical traits like iris, finger, and palm. All these traits are treated independently, and feature of these traits are extracted using two algorithms separately.


2014 ◽  
Vol 207 (2) ◽  
pp. 218-225 ◽  
Author(s):  
Kristen D. Trinca ◽  
Tiffany C. Cox ◽  
Jonathan P. Pearl ◽  
E. Matthew Ritter

2013 ◽  
Vol 753-755 ◽  
pp. 3033-3038
Author(s):  
Yong Bin You ◽  
Ting Ting Li

As an important branch of multi-sensor information fusion, image fusion has been applied in many areas. During the past years, many algorithms have been proposed to solve the fusion issue. However, research on the objective performance evaluation of image fusion is relatively less. Basic methods for image fusion evaluation usually include subjective evaluations and objective evaluations. The evaluation of fused images is regarded as multi-attribute decision-make problem, thus a novel synthesis approach using grey intuitionistic fuzzy sets is proposed. The proposed approach constructs the membership function and non-membership function by the grey correlation degree, thus the intuitionistic fuzzy sets are established. The results show that the proposed approach has better performance.


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