This document proposes a multimodal biometric security system that combines fingerprint, speech, and face recognition for authentication. It discusses different biometric techniques including fingerprint, face, and speech recognition and describes the modules involved in a multimodal system, such as the sensor, feature extraction, matching, and decision making modules. Different levels of data fusion are also covered, including sensor, feature, matching score, and decision level fusion. The document concludes that a multimodal system can improve performance over unimodal systems by reducing false acceptance and rejection rates, while increasing security.
Multimodal biometric systems are those that utilize more than one physical or behavioural characteristic for enrolment , verification, or identification.
One of the most helpful presentation for academic and non academic purpose. This presentation can be presented for 40-45 mins. It contains both technical and non technical details of working of a fingerprint bio-metric scanner.
Multimodal biometric systems are those that utilize more than one physical or behavioural characteristic for enrolment , verification, or identification.
One of the most helpful presentation for academic and non academic purpose. This presentation can be presented for 40-45 mins. It contains both technical and non technical details of working of a fingerprint bio-metric scanner.
Star Link Communication Pvt. Ltd., India's leading manufacturer of biometric attendance system and access control system, brings you this slideshow about biometrics and how the technology works.
First of all, Thank you for giving this opportunity of presenting my knowledge with you all, hope this is helpful to learn something regarding biometric technology
Keystroke dynamics, or typing dynamics, is the detailed timing information that describes exactly when each key was pressed and when it was released as a person is typing at a computer keyboard.
Star Link Communication Pvt. Ltd., India's leading manufacturer of biometric attendance system and access control system, brings you this slideshow about biometrics and how the technology works.
First of all, Thank you for giving this opportunity of presenting my knowledge with you all, hope this is helpful to learn something regarding biometric technology
Keystroke dynamics, or typing dynamics, is the detailed timing information that describes exactly when each key was pressed and when it was released as a person is typing at a computer keyboard.
Paper multi-modal biometric system using fingerprint , face and speechAalaa Khattab
Biometric system is often not able to meet the desired performance requirements.
In order to enable a biometric system to operate effectively in different applications and environments, a multimodal biometric system is preferred.
In this paper introduce a multimodal biometric system which integrates fingerprint verification , face recognition and speaker verification.
Role of fuzzy in multimodal biometrics systemKishor Singh
Person identification is possible through the biometrics using their physiological and behavioral characteristics such
as face, ear, thumb print, voice, signature and key stock. Unimodal biometric systems face a range of problems, including noisy
data, intra-class versions, small liberty, non-university, spoof assaults, and unsustainable error rates. Some of these drawbacks
can be overcome by multimodal biometric technologies, which incorporate data from various information sources. In this paper
we work on multimodal biometric using three modalities face, ear and foot to find the optimal results using fuzzy fusion
mechanism and produces final identification decision via a fuzzy rules that enhance the quality of multimodalities biometric
system.
The Survey of Architecture of Multi-Modal (Fingerprint and Iris Recognition) ...IJERA Editor
Biometrics based individual identification is observed as an effective technique for automatically knowing, with a high confidence a person’s identity. Multi-modal biometric systems consolidate the evidence accessible by multiple biometric sources and normally better recognition performance associate to system based on a single biometric modality.Multi biometric systems are used to overcome this issue by providing multiple pieces of indication of the same identity. This system provides effective fusion structure that combines information provided by the multiple field experts based on decision-level and score-level fusion method, thereby increasing the efficiency which is not conceivable in uni-modal system.Multi-modal biometrics can be attained through a fusion of two or more images, where the subsequent fused image will be more protected. This paper discusses various fusion techniques, architecture of multi-modal biometric authentication and working of biometric fusion i.e. Iris and Fingerprint recognition that are used in multi-modal biometrics
In the age of Biometric Security taking over the traditional security features, this is a small intro to the Biometric features one can use to enhance the security. The various modalities have been explained.
This is a complete report on Bio-metrics, finger print detection. It include what finger print is, how to scan and refin finger print, how the mechanism of its detection work, applications, etc
Verification or Authentication systems use a single biometric sensor which having higher error rate due to single evidence of identity (voice can be change due to cold, face can be changed due facial hairs, cosmetics, fingerprint can be change due to scar etc.). To enhance the performance of single biometric systems in these situations may not be effective because of these problems. Multi-biometric systems overcome some of these limitations by providing multiple proofs of any identity. This paper presents an effective multimodal biometric system which can be used to reduce the above mentioned drawbacks of unimodal systems.
BIOMETRIC BASED AUTHENTICATION SYSTEM TECHNOLOGY
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Biometric system is a pattern identification system that recognizes an individual by determining the originality of the physical features and behavioral characteristic of that person. Of all the recently used biometric techniques, fingerprint identification systems have gained the most popularity because of the prolonged existence of fingerprints and its extensive use. Fingerprint is dependable biometric trait as it is an idiosyncratic and dedicated. It is a technology that is increasingly used in various fields like forensics and security purpose. The vital objective of our system is to make ATM transaction more secure and user friendly. This system replaces traditional ATM cards with fingerprint. Therefore, there is no need to carry ATM cards to perform transactions. The money transaction can be made more secure without worrying about the card to be lost. In our system we are using embedded system with biometrics i.e r305 sensor and UART microcontroller. The Fingerprint and the user_id of all users are stored in the database. Fingerprints are used to identify whether the Person is genuine. A Fingerprint scanner is used to acquire the fingerprint of the individual, after which the system requests for the PIN (Personal Identification Number). The user gets three chances to get him authenticated. If the fingerprints do not match further authentication will be needed. After the verification with the data stored in the system database, the user is allowed to make transactions.
Mobile Authentication with biometric (fingerprint or face) in #AndroidAppDeve...Harikrishna Patel
Biometric identification and authentication depends on unique biological attributes, such as a fingerprint, an iris, a face or even a heartbeat. These attributes are much more difficult for hackers and criminals to exploit because they’re unique to each individual.
Today’s biometric identification and authentication systems cover checks to verify that the biometric elements aren’t coming from video or audio recordings as well. #androidappdevelopment #iotplatform #Softqube
https://www.softqubes.com/blog/mobile-authentication-with-biometric-fingerprint-or-face-in-android/
Personal identification using multibiometrics score level fusioneSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Firstly used on the Automated Fingerprint Identification Systems (AFIS), fingerprint biometrics is now adapted to parallel markets such as Physical Access Control, Logical Access Control, Secured Payment Solutions and applications OEM. These devices profit from the vast expertise acquired by AFIS systems, while using the latest technology.
With the growth of technology their grows threat to our data which is just secured by passwords so to make it more secure biometrics came into existence. As biometric systems are adopted and accepted for security purpose for various information and security systems. Hence it is immune to attacks. This paper deals with the security of biometric details of individuals. In this paper we will be discussing about biometrics and its types and the threats and security issues which is not talked about usually. The different technologies evolved and had contributed to biometrics in long run and their effects. Sushmita Raulo | Saurabh Gawade "Security Issues Related to Biometrics" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd44951.pdf Paper URL: https://www.ijtsrd.com/computer-science/computer-security/44951/security-issues-related-to-biometrics/sushmita-raulo
Biometrics is the science and technology of
measuring and analyzing biological data. In information
technology, biometrics refers to technologies that measure and
analyze human body characteristics, such as DNA, fingerprints,
eye retinas and irises, voice patterns, facial patterns and hand
measurements, for authentication purposes. This paper is about
the applications of biometric especially in the field of healthcare
and its future uses
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
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Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Fundamentals of Electric Drives and its applications.pptx
MULTIMODAL BIOMETRIC SECURITY SYSTEM
1. Efficient Methods of Multimodal Biometric
Security System-
Fingerprint Authentication,
Speech and Face Recognition
SUBMITTED BY:
MAYANK PAL
2. ABSTRACT
This presentation proposes the efficient methods in multimodal biometric i.e. fingerprint,
speech, face.
Multimodal system is developed through fusion of fingerprint, speech and face recognition.
The proposed system is designed for applications where the training database contains a face,
fingerprint images and voice data .
The multimodal biometric security system may be used in various application areas such as, for
authentication number of employees working in offices, in military applications and also in all
possible security applications.
3. CONTENT
I. Introduction of Biometrics
II. Aim
III. Methodology
IV. Multimodal Biometric Systems
V. Biometric Techniques
VI. Modules in Multimodal Biometric Systems
VII. Levels of Fusion
VIII.Result
IX. Conclusion
X. Bibliography
4. INTRODUCTION
The term biometric is usually associated with the use of unique physiological characteristics to
identify an individual. One of the applications which most people associate with biometrics is
security.
It is an automated method of recognizing a person based on a physiological or behavioral
characteristic such as face ,fingerprints, hand geometry, handwriting, iris, voice etc.
As password or PIN can lost or forgotten, biometrics cannot be forgotten or lost and requires
physical presence of the person to be authenticated.
Thus personal authentication systems using biometrics are more reliable, convenient and
efficient than the traditional identification methods.
5. However, even the best biometric traits till date are facing numerous problems biometric
authentication systems generally suffer from enrolment problems due to non-universal
biometric traits, susceptibility to biometric spoofing or insufficient accuracy caused by noisy
data acquisition in certain environments.
Thus to overcome these problems ,multimodal biometric system can be used to reduce/remove
the limitations of unimodal systems.
6. AIM
As the level of security breaches and transaction fraud increases, the need for highly secure
identification and personal verification technologies is becoming apparent.
In recent years, biometrics authentication has seen considerable improvements in reliability
and accuracy, with some of the traits offering good performance.
The reason to combine different modalities is to improve recognition rate.
The aim of multimodal biometrics is to reduce one or more of the following:
FAR(False Acceptance Rate) : It is a measure of the percent of invalid inputs that are
incorrectly accepted.
7. FRR(False Reject Rate) : It is a measure of the percent of valid inputs that are incorrectly
rejected.
CER(Crossover Error Rate) : The rate at which both the accept and reject errors are equal.
- a lower value of the CER is more accurate for Biometric System.
8. MULTIMODAL BIOMETRIC SYSTEMS
Multimodal biometric systems are those that utilize more than one physiological or behavioural
characteristic for enrolment , verification, or identification.
In applications such as border entry/exit, access control, civil identification, and network
security, multi-modal biometric systems are looked to as a means of reducing false non-match
and false match rates, providing a secondary means of enrolment , verification, and
identification.
A multi biometric system uses multiple sensors for data acquisition. This allows capturing
multiple samples of a single biometric trait (called multi-sample biometrics) and/or samples of
multiple biometric traits (called multi source or multimodal biometrics).
9. A unimodal biometric system consists of three major modules: sensor module, feature
extraction module and matching module. The performance of a biometric system is largely
affected by the reliability of the sensor used and the degrees of freedom offered by the features
extracted from the sensed signal.
Further, if the biometric trait being sensed or measured is noisy (a fingerprint with a scar or a
voice altered by a cold, for example), the resultant matching score computed by the matching
module may not be reliable. This problem can be solved by installing multiple sensors that
capture different biometric traits. Such systems, known as multimodal biometric systems , are
expected to be more reliable due to the presence of multiple pieces of evidence.
10. BIOMETRIC TECHNIQUES
FINGERPRINT TECHNOLOGY:
It is the oldest and most widely used method.
It needs a fingerprint reader.
Registered points are located and compared.
Optical sensors are used for scanning purpose.
It can be used for many applications like pc login security, voting system, attendance system
etc.
Uses the ridge endings and bifurcation's on a persons finger to plot points known as Minutiae
The number and locations of the minutiae vary from finger to finger in any particular person,
and from person to person for any particular finger
11. Finger
Image
Finger Image + Minutiae Minutiae
FACE RECOGNITION TECHNOLOGY:
Face Recognition is a biometric technique for automatic identification or verification of a
person from a digital image.
These include the position/size/shape of the eyes, nose, cheekbones and jaw line.
12.
13. SPEECH RECOGNITION TECHNOLOGY:
It is a biometric process of validating a user's claimed identity using characteristics
extracted from their voices.
It uses the pitch, pattern, tone, frequency, rhythm of speech for identification purposes.
During the enrollment phase, the spoken words are converted from analog to digital
format, and the distinctive vocal characteristics such as pitch, frequency, and tone, are
extracted, and a speaker model is established.
A template is then generated and stored for future comparisons.
15. MODULES IN MULTIMODEL BIOMETRIC SYSTEM
A common biometric system mainly involves the following major modules-
1. Sensor Module
At sensor module a suitable user interface incorporating the biometric sensor or scanner is needed
to measure or record the raw biometric data of the user. This raw biometric data is captured and
then it is transferred to the next module for feature extraction. The design of the sensor module
influences the various factors like cost and size.
2. Feature Extraction Module
At feature extraction module the quality of the acquired biometric data from the sensor is assessed
initially for further processing. Thus generating a synoptic but indicative digital representation of
the underlying traits or modalities. After extracting the features it is given as input to the matching
module for further comparison.
16. 3. Matching Module
The extracted features when compared with the templates in the database generate a match score.
This match score may be controlled by the quality of the given biometric data. The matching
module also condensed a decision making module in which the generated match score is used to
validate the claimed identity.
4. Decision making module
Decision making module identifies whether the user is a genuine user or an impostor based on the
match scores. These are used to either validate the identity of a person or provides a ranking of the
enrolled identities for identifying an individual.
17. A simple block diagram for multi-modal biometric system is shown in Fig
18. MODE OF OPERATION
The two major mode of operation in multi-modal biometric systems are
Serial mode
Parallel mode
In serial mode of operation, multiple sources of information is not acquired simultaneously,
that is the user goes through stage by stage authentication process.
Thus the recognition time is improved in serial mode as decision is made before getting all the
traits.
In case of parallel mode of operation, recognition is performed by acquiring multiple sources o
information simultaneously.
This will reduce the efficiency of the system and in turn cause inconvenience to the user.
Study reveals that combined use of both modes may result a system which provides high
efficiency and user convenience.
21. LEVELS OF FUSION
By employing the information available in any of the modules like sensor level, feature
extraction level, matching level and Decision making level, fusion can be developed in multi-
modal biometric system like sensor level fusion, feature level fusion, matching score level
fusion and decision level fusion.
The different biometric identifier used in the multimodal biometric system, their information
from the individual identifier is taken together and can be fused at different levels of fusion
such as fusion at sensor level , fusion at feature level, fusion at matching score level and the
fusion at decision level
22. The following figure shows the fusion at Sensor level which involves combining raw data from
various sensors and this fusion can be appropriate for multi-sample and multi-sensor systems
Fig. Sensor level
23. Feature level fusion shown in Fig refers to combining the different feature sets extracted from
multiple biometric modalities into a single feature vector.
Fig. Feature level fusion
24. Matching score level fusion shown in Fig refers to the combination of similarity scores
provided by a matching module for each input features and template biometric feature
vectors in the database.
Fig. Matching score level fusion
25. In decision level fusion as shown in Fig, the information integration occurs when each
biometric system makes an independent decision about the identity of the user or verifies the
claimed identity.
Fig: Decision level fusion
26. RESULT
A multimodal biometrics system helps us to reduce:
• False accept rate (FAR)
• False reject rate (FRR)
• Failure to enrol rate (FTE)
It also increases:
• Sensor cost
• Enrolment time
• Transit times
• Need for a prior knowledge/data
• System development and complexity
27. CONCLUSION
Though there are many multi-modal biometric systems in practice for authentication of a
person, selection of appropriate modal, choice of optimal fusion level and redundancy in the
extracted features are still some of the shortcomings faced in the design of multi-modal
biometric system that needs to be addressed.
The different approaches that are possible in multi-modal biometric systems, the suitable
fusion levels, and the integration strategies that can be chosen to consolidate information
were discussed.
The combination of more than one biometrics can apply to enhance the security.
Performance and the advanced security level made the multi-modal biometric systems
popular in these days and has great scope in future.
28. 1. L. Hong, A. Jain & S. Kumar, Can multimode biometric Improve performance,
Proceedings of Auto ID 99, pp. 59-64, 1999.
2. A. Ross & A. K. Jain, Information Fusion in Biometrics, Pattern Recognition
Letters, 24 (13), pp. 2115-2125, 2003.
3. A.S. & A. A. Raza , Combined Classifier for Invariant Face Recognition,
Pattern Analysis and Applications, 3(4), pp. 289-302, 2000
4. [A. Ross, A. K. Jain & J.A. Riesman, Hybrid fingerprint matcher, Pattern
Recognition, 36, pp. 1661–1673, 2003
5. W. T. Tan & A. K. Jai , Combining Face and Iris Biometrics for Identity
Verification, Proceedings of Fourth International Conference on AVBPA, pp.
805-813, 2003
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