Contemporary Biometric System Design

2020 ◽  
pp. 292-324
Author(s):  
Himanshu Purohit ◽  
Pawan K Ajmera
Keyword(s):  
Artificial Intelligence ◽  
Noisy Data ◽  
Error Rates ◽  
Biometric System ◽  
Behavioral Traits ◽  
Biometric Systems ◽  
Physical Traits ◽  
Multiple Scenarios ◽  
Different Levels ◽  
Multimodal Biometric Systems

Individual's Identity Authentication depends on physical traits like face, iris, and fingerprint, etc., or behavioral traits like voice and signature. With the rapid advancement in the field of biometrics, multimodal biometric systems are replacing unimodal biometric systems. As the application of molecular biometric system removes certain errors like noisy data, interclass variations, spoof attacks, and unacceptable error rates as compared to unimodal biometric systems. Even the possibilities of multiple scenarios present in multimodal biometric systems are quite helpful for the consolidation of information using different levels of fusion. In this chapter, the authors try to analyze the technological change which is present due to growing field of biometrics with artificial intelligence and undergone a thorough research for multimodal biometric systems for effective authentication purpose. This study is quite helpful for getting different perception for the use of biometrics as a highest level of network security due to the fusion of many different modalities.

Multimodal biometric system using deep learning based on face and finger vein fusion

2021 ◽  
pp. 1-13
Author(s):  
Shikhar Tyagi ◽  
Bhavya Chawla ◽  
Rupav Jain ◽  
Smriti Srivastava
Keyword(s):  
High Performance ◽  
Recognition Accuracy ◽  
Error Rates ◽  
Facial Features ◽  
Biometric System ◽  
Deep Convolutional Neural Networks ◽  
Finger Vein ◽  
Biometric Systems ◽  
Overall Performance ◽  
Recognition Systems

Single biometric modalities like facial features and vein patterns despite being reliable characteristics show limitations that restrict them from offering high performance and robustness. Multimodal biometric systems have gained interest due to their ability to overcome the inherent limitations of the underlying single biometric modalities and generally have been shown to improve the overall performance for identification and recognition purposes. This paper proposes highly accurate and robust multimodal biometric identification as well as recognition systems based on fusion of face and finger vein modalities. The feature extraction for both face and finger vein is carried out by exploiting deep convolutional neural networks. The fusion process involves combining the extracted relevant features from the two modalities at score level. The experimental results over all considered public databases show a significant improvement in terms of identification and recognition accuracy as well as equal error rates.

Verification of Multimodal Biometric

2018 ◽  
pp. 147-193
Author(s):  
Shashidhara H. R. ◽  
Siddesh G. K.
Keyword(s):  
Multimodal Systems ◽  
Biometric Systems ◽  
Physical Traits ◽  
Reliability And Robustness ◽  
Secure Authentication ◽  
Physical Trait ◽  
Multimodal Biometric Systems

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.

Multimodal Biometric System and Information Fusion

2013 ◽  
pp. 48-68 ◽  
Keyword(s):  
Information Fusion ◽  
Fusion Method ◽  
Biometric System ◽  
Operational Parameters ◽  
Multimodal Biometric System ◽  
Biometric Systems ◽  
Fuzzy Fusion ◽  
Different Sources ◽  
Multimodal Biometric Systems

Integrating different information originating from different sources, known as information fusion, is one of the main factors of designing a biometric system involving more than one biometric source. In this chapter, various information fusion techniques in the context of multimodal biometric systems are discussed. Usually, the information in a multimodal biometric system can be combined in senor level, feature extraction level, match score level, rank level, and decision level. There is also another emerging fusion method, which is becoming popular—the fuzzy fusion. Fuzzy fusion deals with the quality of the inputs or with the quality of any system components. This chapter discusses the associated challenges related to making the choice of appropriate fusion method for the application domain, to balance between fully automated versus user defined operational parameters of the system and to take the decision on governing rules and weight assignment for fuzzy fusion.

scholarly journals A Survey on Unimodal, Multimodal Biometrics and Its Fusion Techniques

2018 ◽  
Vol 7 (4.36) ◽  
pp. 689 ◽  
Author(s):  
A. S. Raju ◽  
V. Udayashankara
Keyword(s):  
Information Fusion ◽  
Human Identification ◽  
Future Research ◽  
Biometric System ◽  
Multimodal Biometrics ◽  
Multimodal Biometric System ◽  
Face Features ◽  
Biometric Systems ◽  
Characteristic Sequences ◽  
Multimodal Biometric Systems

Presently, a variety of biometric modalities are applied to perform human identification or user verification. Unimodal biometric systems (UBS) is a technique which guarantees authentication information by processing distinctive characteristic sequences and these are fetched out from individuals. However, the performance of unimodal biometric systems restricted in terms of susceptibility to spoof attacks, non-universality, large intra-user variations, and noise in sensed data. The Multimodal biometric systems defeat various limitations of unimodal biometric systems as the sources of different biometrics typically compensate for the inherent limitations of one another. The objective of this article is to analyze various methods of information fusion for biometrics, and summarize, to conclude with direction on future research proficiency in a multimodal biometric system using ECG, Fingerprint and Face features. This paper is furnished as a ready reckoner  for those researchers, who wish to persue their work in the area of biometrics.  

MODERN INFORMATICS: FROM ROBOTICS TO ARTIFICIAL INTELLIGENCE

2018 ◽  
Vol 1 (8) ◽  
pp. 2-5 ◽  
Author(s):  
L. L. Bosova ◽  
N. N. Samylkina
Keyword(s):  
Artificial Intelligence ◽  
Different Levels

The article describes the work of Informatics Club in the framework of the project "Children University of MPSU". It is considered how it is possible to realize the development of complex questions of informatics in the framework of Club work with students of different levels of education.

scholarly journals Gradient Profile Estimation Using Exponential Cubic Spline Smoothing in a Bayesian Framework

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 674
Author(s):  
Kushani De De Silva ◽  
Carlo Cafaro ◽  
Adom Giffin
Keyword(s):  
State Of The Art ◽  
Estimation Method ◽  
Synthetic Data ◽  
Noisy Data ◽  
Bayesian Framework ◽  
Physical Systems ◽  
Gradient Profile ◽  
Ill Posed ◽  
Profile Estimation ◽  
Different Levels

Attaining reliable gradient profiles is of utmost relevance for many physical systems. In many situations, the estimation of the gradient is inaccurate due to noise. It is common practice to first estimate the underlying system and then compute the gradient profile by taking the subsequent analytic derivative of the estimated system. The underlying system is often estimated by fitting or smoothing the data using other techniques. Taking the subsequent analytic derivative of an estimated function can be ill-posed. This becomes worse as the noise in the system increases. As a result, the uncertainty generated in the gradient estimate increases. In this paper, a theoretical framework for a method to estimate the gradient profile of discrete noisy data is presented. The method was developed within a Bayesian framework. Comprehensive numerical experiments were conducted on synthetic data at different levels of noise. The accuracy of the proposed method was quantified. Our findings suggest that the proposed gradient profile estimation method outperforms the state-of-the-art methods.

Performance of Multimodal Biometric Systems Using Face and Fingerprints (Short Survey)

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

scholarly journals Study of Second and Fourth Digit Lengths and Their Ratios With Physical Attributes in Nepali Population

2018 ◽  
Vol 16 (2) ◽  
pp. 78-81
Author(s):  
Biswas Satyal ◽  
Abhishek Satyal
Keyword(s):  
Ring Finger ◽  
The Body ◽  
Behavioral Traits ◽  
Digit Ratios ◽  
Hand Deformities ◽  
Significant Difference ◽  
Physical Attributes ◽  
Physical Traits ◽  
Left And Right ◽  
Males And Females

Introduction: The ratio of the lengths of the index and the ring finger (2D:4D ratio) is generally different between men and women. A number of studies have shown a correlation between the 2D:4D digit ratio and various physical and behavioral traits. The aim of the present study is to investigate the association of the index (2nd) and ring (4th) digit ratios with some physical traits in Nepal population. Material & Method: 200 students (100 males and 100 females) between ages of 18 years and above were randomly selected with exclusion of those with hand deformities. The digit lengths were measured from the basal crease to the tips usingvernier calipers. The 2D:4D ratios were determined for each subject while height and weight were used to calculate the body mass index and data analyzed. The study was conducted between January 2018 to November 2018. Result: The result of the anthropometric study of the differences in index (2D) and ring (4D) and their ratios shows that there was a significant difference between the length of index finger (2D), ring finger (4D) and the ratios of right hand's 2D:4D in both males and females. There was appositive correlation between the second digit length and Height and weight in males and females both on right and left sides. The 2D:4D ratio for both left and right hand did not show any positive correlation with height, weight or BMI of an individual.

scholarly journals Multimodal Biometric Systems - Study to Improve Accuracy and Performance

2010 ◽  
Vol 1 (2) ◽  
pp. 54-61 ◽  
Author(s):  
K Sasidhar ◽  
Vijaya L Kakulapati ◽  
Kolikipogu Ramakrishna ◽  
K KailasaRao
Keyword(s):  
Biometric Systems ◽  
Improve Accuracy ◽  
And Performance ◽  
Multimodal Biometric Systems

scholarly journals Measuring Digital Transformation Maturity of Supply Chain

2021 ◽  
Vol 15 (2) ◽  
pp. 199-204
Author(s):  
Krešimir Buntak ◽  
Matija Kovačić ◽  
Maja Mutavdžija
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Supply Chain ◽  
Industry 4.0 ◽  
Digital Transformation ◽  
Strategic Decision ◽  
Traditional Practices ◽  
Long Run ◽  
Efficiency And Effectiveness ◽  
Different Levels

Digital transformation signifies changes in all components and systems of the supply chain. It is also a strategic decision of the organization which, in the long run, can result in the creation of competitive advantage in the market. Digital transformation is affecting all organizations, regardless of their activity. Digital transformation of the supply chain involves the use of industry 4.0 based technologies as well as the replacement of traditional practices with new ones based on digital solutions. The implementation of digital solutions, such as artificial intelligence, IoT, cloud computing, etc., therefore, improve communication between stakeholders in the supply chain, as well as improve efficiency and effectiveness. When conducted, digital transformation must be measured by different levels of maturity. In this paper, authors research current models of measuring digital transformation maturity in supply chain and propose a new model based on identified theories and needs.

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