Visionics provides an overview of visionics and facial recognition technology. It discusses the technology, standards, limitations, applications and advantages of visionics, and considers whether visionics and biometrics are the future. Specifically, it covers retinal scan, iris scan, fingerprint, signature and voice recognition. It also discusses vendors like Visionics, challenges like accuracy rates, and applications in security, law enforcement, and ID systems.
The document discusses various types of biometric technologies, including physiological and behavioral biometrics. It provides examples of common biometrics like fingerprint recognition and face recognition. It then describes several emerging or less common biometric technologies in more detail, such as DNA recognition, retina recognition, thermograms, gait analysis, keystroke recognition, ear recognition, skin reflection analysis, and lip motion analysis. The document also briefly discusses future challenges and possibilities for using biometrics.
Identification Simplified - An Introduction to BiometricsAbhishek Mishra
The document discusses various methods of biometric identification that are more secure than traditional ID cards, passwords, etc. It describes iris recognition, voice recognition, face recognition, and fingerprint authentication in detail, explaining how each works, its advantages, and potential applications. While biometric identification has benefits over previous methods, some biometric traits may not work for certain individuals due to physical conditions. Overall, the document promotes biometric identification as a more reliable and secure way to uniquely identify individuals.
This document provides an overview of biometrics including what biometrics is, why it is used, the history of biometrics, common biometric techniques (e.g. fingerprints, iris scans, facial recognition), and advantages and disadvantages of each technique. It discusses identification vs verification uses of biometrics and covers physical, behavioral, and emerging biometric methods. The document concludes that biometrics provides desirable security characteristics and will continue growing in use for mobile devices, buildings, and more in the coming years.
This document discusses various biometric techniques for security and identification. It introduces biometrics as using physiological or behavioral human traits to identify individuals. Some key biometric traits discussed include fingerprints, face recognition, iris scanning, voice recognition, and hand geometry. The document outlines the basic characteristics, workings, advantages, and applications of different biometric techniques. It also notes some biometric traits that are still in development and discusses limitations of certain approaches.
Biometrics refers to using unique human physiological or behavioral characteristics to identify or verify individuals. The document discusses various biometric technologies including fingerprint, face, retina, iris, and signature recognition. It explains how biometric systems work through identification, which compares an unknown biometric to many in a database, and verification, which compares a biometric to a single enrolled template. The advantages of security and convenience are weighed against disadvantages such as cost, changes over time, and user acceptance of different methods.
The document discusses iris biometrics and an iris recognition system. It provides details on iris anatomy, image acquisition, preprocessing, iris localization including pupil and iris detection, iris normalization, feature extraction using Haar wavelets, and matching. It evaluates the system on three databases achieving over 94% accuracy with low false acceptance and rejection rates. Further work is proposed on fusion, dual extraction approaches, indexing large databases, and using local descriptors.
in terms of Forensic Science, how iris recognition is done and what are the key factors that should be kept in mind. It can be its Advantages, Disadvantages, Approaches and very importantly the working process.
The document discusses various types of biometric technologies, including physiological and behavioral biometrics. It provides examples of common biometrics like fingerprint recognition and face recognition. It then describes several emerging or less common biometric technologies in more detail, such as DNA recognition, retina recognition, thermograms, gait analysis, keystroke recognition, ear recognition, skin reflection analysis, and lip motion analysis. The document also briefly discusses future challenges and possibilities for using biometrics.
Identification Simplified - An Introduction to BiometricsAbhishek Mishra
The document discusses various methods of biometric identification that are more secure than traditional ID cards, passwords, etc. It describes iris recognition, voice recognition, face recognition, and fingerprint authentication in detail, explaining how each works, its advantages, and potential applications. While biometric identification has benefits over previous methods, some biometric traits may not work for certain individuals due to physical conditions. Overall, the document promotes biometric identification as a more reliable and secure way to uniquely identify individuals.
This document provides an overview of biometrics including what biometrics is, why it is used, the history of biometrics, common biometric techniques (e.g. fingerprints, iris scans, facial recognition), and advantages and disadvantages of each technique. It discusses identification vs verification uses of biometrics and covers physical, behavioral, and emerging biometric methods. The document concludes that biometrics provides desirable security characteristics and will continue growing in use for mobile devices, buildings, and more in the coming years.
This document discusses various biometric techniques for security and identification. It introduces biometrics as using physiological or behavioral human traits to identify individuals. Some key biometric traits discussed include fingerprints, face recognition, iris scanning, voice recognition, and hand geometry. The document outlines the basic characteristics, workings, advantages, and applications of different biometric techniques. It also notes some biometric traits that are still in development and discusses limitations of certain approaches.
Biometrics refers to using unique human physiological or behavioral characteristics to identify or verify individuals. The document discusses various biometric technologies including fingerprint, face, retina, iris, and signature recognition. It explains how biometric systems work through identification, which compares an unknown biometric to many in a database, and verification, which compares a biometric to a single enrolled template. The advantages of security and convenience are weighed against disadvantages such as cost, changes over time, and user acceptance of different methods.
The document discusses iris biometrics and an iris recognition system. It provides details on iris anatomy, image acquisition, preprocessing, iris localization including pupil and iris detection, iris normalization, feature extraction using Haar wavelets, and matching. It evaluates the system on three databases achieving over 94% accuracy with low false acceptance and rejection rates. Further work is proposed on fusion, dual extraction approaches, indexing large databases, and using local descriptors.
in terms of Forensic Science, how iris recognition is done and what are the key factors that should be kept in mind. It can be its Advantages, Disadvantages, Approaches and very importantly the working process.
Retinal recognition uses the unique pattern of blood vessels in the retina to identify individuals. It is considered the most reliable biometric since the retina develops randomly and is difficult to alter. However, retinal scanners are invasive, expensive, and not widely accepted. They work by capturing an image of the retina using infrared light and extracting over 400 data points to create a template for identification. Factors like eye movement, distance from the lens, or a dirty lens can cause errors in scanning.
The document discusses biometrics, which uses physical or behavioral characteristics to identify individuals. It describes various biometric modalities like fingerprints, facial recognition, iris scans, and voice recognition. These are increasingly used for security applications like building access, computer login, and banking. Biometrics provides stronger authentication than passwords or ID cards, but has concerns around privacy and implementation costs. Overall, the document argues that multi-modal biometric systems offer greater security and are likely to see continued growth and adoption.
A study of Iris Recognition technology over the in use biometric technologies these days. These Study shows how beneficial the iris technology can be to the Human in future.
I have put all my efforts in this study and have made an simple easy to understand ppt.
This document discusses fingerprint recognition using minutiae-based features. It describes the key stages of fingerprint recognition as pre-processing, minutiae extraction, and post-processing. The pre-processing stage involves image acquisition, enhancement, binarization, and segmentation. Minutiae extraction identifies features like ridge endings and bifurcations. Post-processing performs matching and verification of minutiae features between fingerprints. The document provides details on each stage and techniques used for minutiae-based fingerprint recognition.
The document summarizes iris recognition as a biometric identification method. It describes the anatomy of the human eye and details how the iris has unique patterns that can be used to identify individuals. The summary explains that iris recognition works by imaging the iris, locating its boundaries, normalizing variations, and matching its texture patterns to encoded templates in a database. With over 200 identifying features, the iris provides very high accuracy for identification applications such as border control, ATMs, and computer login authentication.
The document summarizes recent progress in iris recognition technology. It discusses iris image acquisition, preprocessing techniques like localization and normalization, and pattern recognition methods. It also outlines applications of iris recognition in areas like border control, criminal investigations, and secure banking. Emerging areas discussed include long-range iris recognition, multi-biometric systems, and generating synthetic iris images for database construction.
The document discusses iris recognition technology. It begins by introducing iris recognition as a biometric authentication method using pattern recognition on high-resolution eye images. It then provides details on how iris recognition works, including isolating the iris area in an image, encoding the iris patterns into binary templates, and comparing templates to identify or verify individuals. The document also discusses the statistical properties of iris patterns that make iris recognition highly accurate and reliable compared to other biometric methods. It concludes by mentioning some commercial applications of iris recognition technology.
This document discusses iris recognition as a biometric method for uniquely identifying individuals. It begins by explaining biometrics and the need for identification methods due to advances in technology and globalization. It then describes the anatomy of the human eye and details how the iris is unique among individuals and stable over one's lifetime, making it suitable for recognition. The document explains John Daugman's algorithms for iris encoding and matching iris codes to identify individuals. It discusses applications of iris recognition including border control, ATM access, and forensic identification. The document concludes that iris recognition is a highly accurate and secure biometric method due to the statistical rarity of matching irises between individuals.
Iris recognition is an automated method of bio metric identification that uses mathematical pattern-recognition techniques on video images of one or both of the irises of an individual's eyes, whose complex patterns are unique, stable, and can be seen from some distance.
Retinal scanning is a different, ocular-based bio metric technology that uses the unique patterns on a person's retina blood vessels and is often confused with iris recognition. Iris recognition uses video camera technology with subtle near infrared illumination to acquire images of the detail-rich, intricate structures of the iris which are visible externally.
Biometrics uses physiological characteristics like fingerprints, iris patterns, and voice to identify individuals. The iris, located around the pupil, regulates the size of the pupil and has complex random patterns that are unique to each person. Iris recognition uses cameras to capture an iris image, overlay a grid to analyze patterns, and compare it to stored templates to identify a person. Iris scanning is highly accurate for identification and authentication purposes across applications like border control, computer login, and financial transactions due to the iris having unique patterns that remain stable throughout life.
The document discusses the technology of the future. It covers several topics related to biometrics including a brief history, current applications, and the future potential of various biometric technologies such as fingerprints, iris recognition, and voice recognition. The document also discusses how biometric systems work and compares the features and accuracy of different biometric parameters.
The document discusses iris recognition as a biometric identification method. It provides a brief history of iris recognition from its proposal in 1939 to its implementation in 1990 by Dr. John Daugman who created algorithms for it. The document outlines the iris recognition process including iris localization, normalization, feature extraction using Gabor filters, and matching using techniques like Euclidean distance. It discusses advantages like accuracy and stability of iris patterns, and disadvantages such as cost and inability to capture images from certain positions.
Study and development of Iris Segmentation and Normalization TechniqueSunil Kumar Chawla
The document is a thesis presentation on studying and developing iris segmentation and normalization techniques. It contains an introduction to biometrics and iris recognition. The document discusses literature on iris segmentation and normalization methods. It also covers topics like the anatomy and properties of the iris, existing iris recognition systems, and issues regarding biometrics. The goal is to develop an iris recognition system and evaluate its performance.
This document outlines a course syllabus on biometrics that covers 14 topics over multiple lectures. The course introduces common biometric modalities like fingerprint, face, iris, and hand geometry recognition. It discusses the history of biometrics from ancient uses of fingerprints and handprints to modern automated systems. A typical biometric system is described as having sensors, signal processing, data storage, matching, and decision components. Characteristics of effective biometrics like universality, uniqueness, and permanence are also summarized.
This document discusses various types of biometrics that can be used for authentication, including hard biometrics like fingerprints, soft biometrics like build and mannerisms, and behavioral biometrics like gait and typing patterns. It notes that biometrics can be classified based on what is analyzed, such as frequency for speech or speed and pressure for signatures. The document also discusses common biometric sensors, methodologies for analyzing sensor data, and the benefits and disadvantages of different biometric factors and sensors. It promotes the idea that continuous authentication using multiple biometrics can provide more secure access than single-factor authentication.
This document discusses biometrics technology and its various applications. It describes three main types of authentication: something you know, something you have, and something you are (biometrics). Biometrics refers to using biological and behavioral characteristics to identify individuals. Common physical biometrics include fingerprints, facial features, retina, iris, veins and hand/finger geometry. Behavioral biometrics include keystroke dynamics, voice, gait, and signature. The document outlines several biometric technologies like fingerprint, facial, iris recognition and signature identification. It also discusses applications in security, government, banking, access control and advantages and disadvantages of biometrics.
The document discusses iris recognition as a biometric identification method that uses pattern recognition techniques to identify individuals based on the unique patterns in their irises. It provides an overview of the history and development of iris recognition, describes the components of an iris recognition system including image acquisition, segmentation, normalization, and feature encoding, and discusses applications of iris recognition including uses for border control, computer login authentication, and other security purposes.
The document discusses iris recognition as the best biometric identification system. It provides an overview of the iris recognition process which involves iris localization, normalization, feature encoding, and matching. Real-world applications of iris recognition include the Aadhaar ID project in India and border security in the UAE. While highly accurate, iris recognition has some disadvantages like accuracy variations depending on imaging conditions and potential for fake iris lenses. Overall, iris recognition is described as a fast and accurate biometric technology that will become more common with further development to address current limitations.
The document provides an overview of the high tech industry and focuses on several key segments including hardware, software, and services. For hardware, it discusses business and consumer focused offerings such as PCs, chips, storage devices, telecom equipment, and more. For software, it outlines infrastructure, enterprise, and consumer applications. And for services, it discusses various business process outsourcing and IT services.
The document discusses face recognition technology as a biometric authentication method. It describes how face recognition works by detecting nodal points on faces and creating unique faceprints. The advantages are that face recognition is convenient, socially acceptable and inexpensive compared to other biometrics. However, face recognition has difficulties with identical twins and environmental/appearance changes reducing accuracy over time. The document also outlines applications in security, law enforcement, banking, and commercial access control.
Retinal recognition uses the unique pattern of blood vessels in the retina to identify individuals. It is considered the most reliable biometric since the retina develops randomly and is difficult to alter. However, retinal scanners are invasive, expensive, and not widely accepted. They work by capturing an image of the retina using infrared light and extracting over 400 data points to create a template for identification. Factors like eye movement, distance from the lens, or a dirty lens can cause errors in scanning.
The document discusses biometrics, which uses physical or behavioral characteristics to identify individuals. It describes various biometric modalities like fingerprints, facial recognition, iris scans, and voice recognition. These are increasingly used for security applications like building access, computer login, and banking. Biometrics provides stronger authentication than passwords or ID cards, but has concerns around privacy and implementation costs. Overall, the document argues that multi-modal biometric systems offer greater security and are likely to see continued growth and adoption.
A study of Iris Recognition technology over the in use biometric technologies these days. These Study shows how beneficial the iris technology can be to the Human in future.
I have put all my efforts in this study and have made an simple easy to understand ppt.
This document discusses fingerprint recognition using minutiae-based features. It describes the key stages of fingerprint recognition as pre-processing, minutiae extraction, and post-processing. The pre-processing stage involves image acquisition, enhancement, binarization, and segmentation. Minutiae extraction identifies features like ridge endings and bifurcations. Post-processing performs matching and verification of minutiae features between fingerprints. The document provides details on each stage and techniques used for minutiae-based fingerprint recognition.
The document summarizes iris recognition as a biometric identification method. It describes the anatomy of the human eye and details how the iris has unique patterns that can be used to identify individuals. The summary explains that iris recognition works by imaging the iris, locating its boundaries, normalizing variations, and matching its texture patterns to encoded templates in a database. With over 200 identifying features, the iris provides very high accuracy for identification applications such as border control, ATMs, and computer login authentication.
The document summarizes recent progress in iris recognition technology. It discusses iris image acquisition, preprocessing techniques like localization and normalization, and pattern recognition methods. It also outlines applications of iris recognition in areas like border control, criminal investigations, and secure banking. Emerging areas discussed include long-range iris recognition, multi-biometric systems, and generating synthetic iris images for database construction.
The document discusses iris recognition technology. It begins by introducing iris recognition as a biometric authentication method using pattern recognition on high-resolution eye images. It then provides details on how iris recognition works, including isolating the iris area in an image, encoding the iris patterns into binary templates, and comparing templates to identify or verify individuals. The document also discusses the statistical properties of iris patterns that make iris recognition highly accurate and reliable compared to other biometric methods. It concludes by mentioning some commercial applications of iris recognition technology.
This document discusses iris recognition as a biometric method for uniquely identifying individuals. It begins by explaining biometrics and the need for identification methods due to advances in technology and globalization. It then describes the anatomy of the human eye and details how the iris is unique among individuals and stable over one's lifetime, making it suitable for recognition. The document explains John Daugman's algorithms for iris encoding and matching iris codes to identify individuals. It discusses applications of iris recognition including border control, ATM access, and forensic identification. The document concludes that iris recognition is a highly accurate and secure biometric method due to the statistical rarity of matching irises between individuals.
Iris recognition is an automated method of bio metric identification that uses mathematical pattern-recognition techniques on video images of one or both of the irises of an individual's eyes, whose complex patterns are unique, stable, and can be seen from some distance.
Retinal scanning is a different, ocular-based bio metric technology that uses the unique patterns on a person's retina blood vessels and is often confused with iris recognition. Iris recognition uses video camera technology with subtle near infrared illumination to acquire images of the detail-rich, intricate structures of the iris which are visible externally.
Biometrics uses physiological characteristics like fingerprints, iris patterns, and voice to identify individuals. The iris, located around the pupil, regulates the size of the pupil and has complex random patterns that are unique to each person. Iris recognition uses cameras to capture an iris image, overlay a grid to analyze patterns, and compare it to stored templates to identify a person. Iris scanning is highly accurate for identification and authentication purposes across applications like border control, computer login, and financial transactions due to the iris having unique patterns that remain stable throughout life.
The document discusses the technology of the future. It covers several topics related to biometrics including a brief history, current applications, and the future potential of various biometric technologies such as fingerprints, iris recognition, and voice recognition. The document also discusses how biometric systems work and compares the features and accuracy of different biometric parameters.
The document discusses iris recognition as a biometric identification method. It provides a brief history of iris recognition from its proposal in 1939 to its implementation in 1990 by Dr. John Daugman who created algorithms for it. The document outlines the iris recognition process including iris localization, normalization, feature extraction using Gabor filters, and matching using techniques like Euclidean distance. It discusses advantages like accuracy and stability of iris patterns, and disadvantages such as cost and inability to capture images from certain positions.
Study and development of Iris Segmentation and Normalization TechniqueSunil Kumar Chawla
The document is a thesis presentation on studying and developing iris segmentation and normalization techniques. It contains an introduction to biometrics and iris recognition. The document discusses literature on iris segmentation and normalization methods. It also covers topics like the anatomy and properties of the iris, existing iris recognition systems, and issues regarding biometrics. The goal is to develop an iris recognition system and evaluate its performance.
This document outlines a course syllabus on biometrics that covers 14 topics over multiple lectures. The course introduces common biometric modalities like fingerprint, face, iris, and hand geometry recognition. It discusses the history of biometrics from ancient uses of fingerprints and handprints to modern automated systems. A typical biometric system is described as having sensors, signal processing, data storage, matching, and decision components. Characteristics of effective biometrics like universality, uniqueness, and permanence are also summarized.
This document discusses various types of biometrics that can be used for authentication, including hard biometrics like fingerprints, soft biometrics like build and mannerisms, and behavioral biometrics like gait and typing patterns. It notes that biometrics can be classified based on what is analyzed, such as frequency for speech or speed and pressure for signatures. The document also discusses common biometric sensors, methodologies for analyzing sensor data, and the benefits and disadvantages of different biometric factors and sensors. It promotes the idea that continuous authentication using multiple biometrics can provide more secure access than single-factor authentication.
This document discusses biometrics technology and its various applications. It describes three main types of authentication: something you know, something you have, and something you are (biometrics). Biometrics refers to using biological and behavioral characteristics to identify individuals. Common physical biometrics include fingerprints, facial features, retina, iris, veins and hand/finger geometry. Behavioral biometrics include keystroke dynamics, voice, gait, and signature. The document outlines several biometric technologies like fingerprint, facial, iris recognition and signature identification. It also discusses applications in security, government, banking, access control and advantages and disadvantages of biometrics.
The document discusses iris recognition as a biometric identification method that uses pattern recognition techniques to identify individuals based on the unique patterns in their irises. It provides an overview of the history and development of iris recognition, describes the components of an iris recognition system including image acquisition, segmentation, normalization, and feature encoding, and discusses applications of iris recognition including uses for border control, computer login authentication, and other security purposes.
The document discusses iris recognition as the best biometric identification system. It provides an overview of the iris recognition process which involves iris localization, normalization, feature encoding, and matching. Real-world applications of iris recognition include the Aadhaar ID project in India and border security in the UAE. While highly accurate, iris recognition has some disadvantages like accuracy variations depending on imaging conditions and potential for fake iris lenses. Overall, iris recognition is described as a fast and accurate biometric technology that will become more common with further development to address current limitations.
The document provides an overview of the high tech industry and focuses on several key segments including hardware, software, and services. For hardware, it discusses business and consumer focused offerings such as PCs, chips, storage devices, telecom equipment, and more. For software, it outlines infrastructure, enterprise, and consumer applications. And for services, it discusses various business process outsourcing and IT services.
The document discusses face recognition technology as a biometric authentication method. It describes how face recognition works by detecting nodal points on faces and creating unique faceprints. The advantages are that face recognition is convenient, socially acceptable and inexpensive compared to other biometrics. However, face recognition has difficulties with identical twins and environmental/appearance changes reducing accuracy over time. The document also outlines applications in security, law enforcement, banking, and commercial access control.
This document proposes implementing a biometric attendance system for a university to more accurately track attendance of students and faculty. The current online attendance system allows for fake attendance to be filled in by others. The proposed biometric system would use thumbprints to register and log in students and staff from different roles like teachers, clerks and lab assistants. It would record attendance information in a backend database server and track attendance for individual classes. The system aims to provide trusted attendance tracking and encourage responsibility and punctuality among students and faculty.
Biometric Attendance System records attendance of employee by using finger print and facial recognition. Biometric Attendance System is more useful than ID card punching and traditional method of attendance i.e. marking attendance in register. Divinity IT Solutions offers biometric attendance systems to companies and organizations who want to record their employee’s attendance accurately.
http://www.divinityit.com/Biometric-Attendance-Device.html
The document discusses the Aadhaar card system implemented in India. It provides background on the Unique Identification Authority of India (UIDAI) which oversees Aadhaar. Aadhaar aims to provide identification to all residents and facilitate access to benefits and services. It discusses the benefits of Aadhaar in reducing leakage in welfare schemes but also acknowledges criticisms around privacy, security of personal data, and reliability of biometric data collection. Overall, the document presents information on both sides of the Aadhaar system debate.
India is one of the largest countries in the world to have the most sophisticated online pure identity verification platform. This biometric based online identity verification platform, will open novel opportunities and industries in the years to come. This presentation gives a broad overview of the project and some of futuristic opportunities which can become possible.
The document provides a bounded case study of India's Aadhaar social welfare program. It summarizes that Aadhaar has enrolled over 750 million Indians in a unified biometric identification system, transforming social welfare delivery. Aadhaar issues a unique ID number linked to biometric data for each recipient. It enables digital verification of recipients and direct bank transfers of benefits to recipients' accounts. This ensures accurate benefit delivery while reducing fraud. The study analyzes strengths and limitations of Aadhaar through 50 scholarly sources to evaluate how it has converted traditional welfare systems into an efficient, accountable and transparent digital system through identification and payment technologies like Aadhaar Payments Bridge and Aadhaar Enabled Payment System.
This document describes a biometric attendance system for government employees in Jharkhand, India. The system uses fingerprint or iris authentication via Aadhaar to record employee check-ins and check-outs in real time. It is affordable, portable, and works over both Wi-Fi and cellular networks. The system prevents backdated entries, tracks hours spent in the office, and allows employees to mark attendance from any location. However, it requires internet connectivity and users must have a valid Aadhaar identification number.
Biometric attendance system is linked with Unique Identification number (Aadhaar) making attendance process secured and eliminating duplicates at the same time. The application is simple to use. The attendance system requires Government employees to register into the attendance system as one time activity. After successful registration system randomly generates a unique 6 digit ID for each registered employees. Employees need to enter this six digit ID along with their Finger print on the installed devices for marking their attendance.
My keynote at the Inbound Marketing Summit, talking about social media, marketing by being part of a community, and "creating more value than you capture."
Influence of Global Trends on Marketing of Local ProductsDr. Martina Olbert
Presentation prepared for a conference International Days of Marketing organized in Marrakech and Guelmim, Morocco. I was asked to speak about global marketing trends influencing better marketing of local products, a topic which marketeers could use for inspiration in marketing of their own local products in competition of global products in Morocco.
This document describes a fingerprint attendance system that uses biometric fingerprint recognition for access control and attendance monitoring. The system utilizes an embedded microcontroller, fingerprint sensor module, GSM module, LCD display and other components. It is designed to accurately identify authorized individuals through their fingerprints in order to maintain attendance records, prevent manipulation, and make cheating impossible. Potential applications of the system include monitoring employee attendance in offices, industries, and other organizations.
Presentation on
-Methods of Cashless payment including recent Govt initiatives e.g. UPI, APES, USSD, APES, eWallets
- Comparison UPI Vs eWallets
- Vulnerabilities of going Cashless
- Safety Tips
Tim O'Reilly discusses the emergence of a global brain through the convergence of computing and connectivity. He asserts that as sensors proliferate and more data and knowledge is shared online, an intelligent network is being built that connects people and information on a global scale. However, this network is not an artificial intelligence but rather an augmentation of human intelligence. O'Reilly argues that we must guide the development of this new system to be resilient and ensure it learns human virtues like morality.
1) The Unified Payments Interface (UPI) allows for simple push and pull payments between banks using only a virtual address like a username.
2) Banks act as Payment Service Providers (PSPs) and provide a single app for all transactions via a single identifier like Aadhaar number with one-click two-factor authentication.
3) UPI provides benefits to end users like privacy by only sharing a virtual address, multiple uses for payments, remittances and bills, and availability 24/7 on personal devices with security.
Dissertation report on customer satisfaction towards rupay cardSardar Ji
RuPay is an Indian domestic debit and credit card scheme launched by NPCI as an alternative to Visa and Mastercard to promote digital payments within India. Major banks like SBI and HDFC issue RuPay cards to customers and the cards can be used at ATMs, point of sale terminals, and online merchants across India. NPCI has an agreement with Discover Financial to enable international acceptance of RuPay cards and has ambitious plans to expand the RuPay network and increase its market share competing with Visa and Mastercard over the next few years.
5 Global Trends That Will Impact Your Marketing Strategies in 2012Factiva
Take a look at 5 economic and cultural trends that will impact your marketing strategies in 2012 and beyond. Beth Tessier, Executive Director of Consumer Insights, and Ellen Desmarais, Executive Director of Digital Strategy bring together the latest research on:
- Urbanization and how its impacts on city growth and geographic expansion affect the way you go to market
- New world of mobilization and the marketing implications you must consider in order to thrive in an m-commerce world
- Proliferation of customer choices and how your customers make decisions in order to help your buyers to make the right ones
- The how, why, and what of online sharing and the marketing strategies you need to consider
- The right balance of global vs. local and how you can successfully operate in a borderless world
This document discusses biometrics and multi-factor authentication. It begins with definitions of multi-factor authentication and biometric authentication. It then covers various categories of biometrics including physiological (iris, finger) and behavioral (keystroke dynamics, gait). The document discusses how well biometrics work based on metrics like false acceptance and false rejection rates. It also covers the FBI Biometrics Center of Excellence and their work evaluating biometric algorithms and collaborating with universities. Trends in biometrics like multimodal biometrics are discussed along with challenges such as spoofing.
The document discusses biometrics and fingerprint recognition technologies. It provides an overview of why biometrics are needed due to vulnerabilities in traditional identity methods like passwords. It then describes different biometric modalities like fingerprints, facial recognition, iris scanning, and compares their characteristics. The document explains how fingerprint recognition works from image capture to matching. It outlines fingerprint matching algorithms and challenges. Finally, it discusses applications of fingerprint biometrics and provides a brief history of biometrics.
It's about biometric system L10A_Savvides_Biometrics.pdfpreethi3173
This document provides an introduction to biometric technologies and applications. It discusses some of the common problems with traditional security systems like passwords, including passwords being forgotten, stolen, or cracked. Biometric technologies provide an alternative for verifying or identifying individuals based on unique physiological or behavioral characteristics. Examples of biometric modalities discussed include fingerprints, face recognition, iris recognition, and voice recognition. Applications of biometric technologies include identification by matching against a database and verification by comparing to an enrolled template.
The document provides an introduction to biometrics, which are automated methods of recognizing a person based on physiological or behavioral characteristics like fingerprints, face, iris, retina, hand geometry, signature, and voice. It discusses different biometric modalities, applications, types of sensors, the biometric system process, how some biometric technologies like fingerprint and facial scanners work, barriers to biometrics adoption, and companies involved in different biometric technologies.
There are three main types of authentication: something you know, something you have, and something you are. Biometrics uses biological and behavioral characteristics to identify individuals, such as fingerprints, iris patterns, voice, gait, and signatures. Some common biometric technologies are fingerprint, face, iris, vein, voice, and signature recognition. Biometrics can be used for applications like access control, time/attendance tracking, airports, ATMs, and more. While biometrics provide security benefits, they also have disadvantages like cost, accuracy issues, and privacy concerns. The field continues to evolve as costs decrease and convenience increases.
This document summarizes different types of biometrics, including physiological and behavioral biometrics. It provides details on common biometrics like fingerprint recognition, face recognition, speaker recognition, and iris recognition. It also discusses less common biometrics still in early stages of development, such as DNA recognition, retina recognition, thermograms, gait analysis, keystroke recognition, ear recognition, skin reflection, lip motion analysis, and body odor analysis. The document compares DNA biometrics to conventional biometrics and provides examples of applications of different biometrics technologies.
This document discusses palm vein recognition technology for biometric authentication. It begins by explaining biometrics and some common biometric techniques like fingerprints, iris scans, and voice recognition. It then introduces palm vein recognition which uses infrared light to scan the unique vein patterns in one's palm. The document details how the palm vein pattern is extracted, encrypted, stored and used for matching during authentication. It notes the advantages of palm vein recognition over other techniques in terms of accuracy, security and inability to forge. Finally, it discusses some applications and challenges of the technology.
This document summarizes a research paper on hand vein authentication systems. It discusses how hand vein patterns are unique biometric identifiers that can be used for authentication. The system works by capturing an image of the veins in the back of the hand, extracting the vein pattern features, and matching the features to authenticate a user. Key advantages of this approach are that vein patterns are difficult to replicate, located inside the hand, and stable over time. The document provides details on the image processing and authentication methodology.
Biometricstechnology in iot and machine learningAnkit Gupta
Ravi Kumar presented on biometrics technology. The presentation discussed what biometrics is, the importance of biometrics for security and convenience, and the history of biometrics. It described various physical and behavioral biometric characteristics like fingerprints, face recognition, iris scans, and voice recognition. Applications of biometrics technology discussed included access control, time and attendance tracking, and use at airports and ATMs. Both advantages like uniqueness and accountability and disadvantages like costs and potential for false readings were covered. Emerging biometric technologies of the future may include ear shape, body odor, and DNA identification.
Biometrics is the science of measuring and analyzing human body characteristics for authentication purposes. Major biometrics include face, fingerprints, and irises. Fingerprints are uniquely persistent and can be used for positive identification through analysis of ridge and minutiae patterns, such as bifurcations and ridge endings. Fingerprint images are typically stored and classified according to international standards that define format, resolution, and quality parameters.
Physical biometrics alludes to physiological elements on the human body that can fill in as ID, for example, a finger impression or retina filter. Organizations frequently gather and store physical biometric information to confirm personalities for a wide range of occupations, security being the clearest. Physical biometric distinguishing proof can likewise have other use situations where facial acknowledgment is utilized to recognize hot shots in a gambling club to further develop their client experience.
This document discusses alternatives to passwords for authentication. It begins by outlining problems with passwords, such as users choosing weak passwords that are hard to remember. It then examines current solutions like biometrics, smart cards, and RFID. The bulk of the document focuses on biometrics, describing various biometric technologies like fingerprints, facial recognition, voice recognition, iris scans, and others. It notes the benefits but also limitations and challenges of each technology. The document also provides an overview of smart cards and RFID as password alternatives.
This document discusses biometrics technology. It defines biometrics as the measurement and analysis of physical and behavioral characteristics to identify individuals. Common physical biometrics include fingerprints, facial recognition, iris scans, and vein patterns. Behavioral biometrics include voice recognition, signatures, and gait. The document outlines the history of biometrics and describes how various biometric techniques like fingerprinting, facial recognition, and iris scans work. It discusses applications of biometrics for access control, airports, ATMs, and more. Both advantages like convenience and security and disadvantages like costs are presented.
The document discusses biometrics, which is the automated measurement and analysis of biological data to identify individuals. It provides an introduction to biometrics and its history, importance, characteristics including physical (e.g., fingerprints, iris) and behavioral (e.g., voice, signature) traits. The biometrics process and applications in security, time/attendance, and access control are described. Advantages include uniqueness and accuracy, while disadvantages include costs and potential for false matches. The future of biometrics is promising with emerging technologies like ear and odor identification.
This document discusses biometrics, which is the measurement and analysis of people's physical and behavioral characteristics for identification purposes. It describes several biometric technologies including fingerprint recognition, facial recognition, voice recognition, iris recognition, retina recognition, and hand geometry. For each technology, it explains the basic process and how unique physical traits are measured and analyzed. The advantages of biometrics are that they cannot be lost, stolen, or forgotten like passwords. However, biometrics also have disadvantages like high costs and potential inaccuracies. Biometrics have applications in security, banking, healthcare, and other fields.
Biometrics can be used for identification and verification purposes through something you know, have, or are. Common biometrics include fingerprints, facial recognition, iris scans, and voice identification. Each biometric has strengths and weaknesses in terms of accuracy, user acceptance, and vulnerability to attacks. Proper system design and oversight are needed to address privacy and civil liberties concerns when using biometrics for identification.
This document discusses various biometric technologies including fingerprint recognition, iris scanning, retina scanning, voice recognition, signature verification, face recognition, and hand geometry recognition. It describes how each type of biometric works, including capturing biometric data, extracting distinguishing features, enrollment, verification, and matching against stored templates. Biometrics are increasingly used for identification and access control because they cannot be lost, stolen, or forgotten like ID cards or passwords. However, biometric systems must also account for changes in biometrics over time.
This document summarizes a research paper on implementing a fingerprint-based biometric authentication system for ATMs using a PIC microcontroller. It describes how fingerprint identification works by analyzing ridge and valley patterns. The system uses a PIC16F877A microcontroller to collect fingerprint data from a fingerprint sensor module and match it to an enrolled fingerprint template to authenticate users. If a match is found, the ATM cashbox opens, and if not, an alarm sounds. The document discusses the methodology, advantages, limitations and components of the system, including the fingerprint sensor, microcontroller, LCD display, motor driver, and buzzer.
The document discusses palm vein biometric authentication technology. It explains that palm vein authentication uses infrared light to scan the unique vein patterns in a person's palm, which are then converted into encrypted data and stored in a database. This provides highly accurate personal identification without physical contact. Palm vein authentication has advantages over other biometric methods in being non-invasive, hygienic, and difficult to fake due to the complexity of palm vein patterns. It is being adopted for uses like ATMs, computers, and hospitals due to its security and contactless features.
This document discusses biometrics, which uses human body characteristics to authenticate identity. It describes how biometric devices work by scanning a trait, converting it to digital form, and comparing it to stored data. There are two main classes of biometrics: physiological (face, fingerprints, iris) and behavioral (signature, voice). Biometrics has advantages like accuracy but also disadvantages like cost and the possibility that some traits may change over time.
This document discusses biometrics, which uses human body characteristics to authenticate identity. It describes biometric devices that scan and digitize characteristics like fingerprints, irises, voice patterns. Biometrics can be physiological (face, fingerprints) or behavioral (signature, voice). To be used for identification, characteristics must be universal, unique, permanent, collectible, and difficult to circumvent. The document outlines various biometric modalities like fingerprint recognition, face recognition, voice recognition, and iris recognition. It also discusses advantages like accuracy but notes disadvantages like cost and changing characteristics with age, disease, or environment.
This document summarizes a webinar presentation about antimicrobial copper surfaces. The presentation discussed the need for antimicrobial surfaces in healthcare settings to prevent infections. It provided an overview of the antimicrobial properties of copper and clinical evidence that copper surfaces continuously kill bacteria and viruses. The presentation also described available copper product options and the results of clinical trials showing that copper surfaces reduce bacteria levels in hospital rooms.
1) In a world of increasing digital communication and shortening attention spans, visual branding remains important for standing out and being remembered.
2) Effective visual branding incorporates target audiences, relevant images and locations, and creative visual media to engage human emotions.
3) While digital interactions are growing, the physical world still plays a key role in building brands through tangible experiences that reinforce messaging and cannot be replicated online.
Verizon and AT&T allow mobile phone customers to pay their bills online. Mobile phone bills represent a large portion of bills paid online as more customers switch from landlines to mobile phones. The number of disconnected landline customers and underbanked individuals contributes to the growth in bill pay for mobile phone services.
The document discusses the continued importance and prevalence of cash usage despite the rise of digital payments. It notes that around 48% of US retail transactions are still made with cash, and cash is used for over half of transactions under $50. While cash does have disadvantages like risk of theft, it remains widely accepted and convenient, especially for younger consumers and for small dollar purchases. The document advocates that businesses should consider automating cash handling to increase efficiency and the customer base by accepting cash. It provides examples of industries that benefit from cash automation like parking, gaming, and bill payment kiosks.
The document discusses how deploying technology like kiosks and digital signage can benefit both customers and businesses by improving efficiency and customer experience. It provides examples of how goals like faster transactions, consistent processes, and cost savings overlap between customers and deployers. Specific examples that got it right include digital directories, signage at shopping malls, workforce information kiosks, and patient check-in kiosks. Key factors for success are picking the right task, a friendly design, simplicity, and following accessibility guidelines. Ultimately, addressing both customer and deployer needs is important for a successful project.
B-cycle is a bike sharing program that provides a convenient transportation alternative for commuters and tourists. It works by installing bike rental kiosks and docking stations that allow users to easily rent and return bikes using RFID technology. The kiosks were custom designed by KIOSK to optimize the user experience and manage the bike inventory. B-cycle has installed over 250 stations across 15 US cities, providing over 3,250 bikes. It has been very successful in promoting alternative transportation and changing commuter behavior.
This document provides an overview of self-service kiosks and retail trends from 2020. It discusses the growing kiosk market size and revenue forecasts. Retail is the largest segment, accounting for about half of total kiosk budgets and units. The document also examines technology trends impacting kiosks and rationales for their use in retail settings. Several retail industries that utilize kiosks are highlighted, including airlines, convenience stores, restaurants, and grocery stores. The conclusions emphasize creating a customer-centric experience across retail channels.
This document provides practical examples of kiosks and considerations for ADA and PCI compliance. It describes configurations such as a kiosk for the Department of Homeland Security using biometrics, a kiosk for Speedway gas stations that uses an encrypted PIN pad and hybrid card reader, and an AT&T bill pay kiosk that isolates credit card processing to a single certified point of sale device. It also gives an example of a gift card kiosk that is a fully validated and certified PCI compliant application.
This document discusses using 3D printing to create custom optical elements, called "Printed Optics", that can be embedded in interactive devices. It presents four categories of Printed Optics fabrication techniques: 1) Light Pipes that can guide light through devices for display purposes, 2) Internal Illumination techniques using hollow spaces, 3) Sensing user input by tracking mechanical movements of printed elements, and 4) Embedding optoelectronic components. The document outlines examples like using light pipes in a mobile projector accessory or sensing touch inputs on a device's surface. Overall, it explores how 3D printing optical elements opens up new possibilities for interaction design.
This document discusses retail self-service kiosks. It defines kiosks as freestanding, interactive multimedia systems that provide information or enable transactions without staff assistance. The kiosk market grew 9.3% annually from 2009 to $740.4 million in 2014 as postponed 2009 projects revived in 2010. New technologies like mobile apps and iPads are seen as opportunities rather than threats. Product vending and loyalty programs are growing applications, while biometrics and sensors show promise but little demand currently. The document analyzes kiosk trends, technologies, applications and market segments.
Kiosk Information Systems is a leading manufacturer of kiosk solutions that will exhibit at the National Retail Federation's Big Show 2012. They provide hardware, software, and field services for over 100,000 self-service kiosks. Kiosk has a diverse customer base across many industries and offers both standard and customized kiosks designed through a certified process. Their experience and flexibility enables them to support a wide range of deployments from small to very large nationwide projects.
The document discusses kiosks and mobile point-of-sale (POS) technologies as emerging channels for integrated marketing strategies. It notes that consumer demands for convenience and increased competition have accelerated the need for innovative multi-channel approaches. Kiosks are identified as a major channel to support integrated marketing. A kiosk implementation requires expertise across many domains and should follow a strategic roadmap. With proper planning, user experience design, technology, and measurement, kiosks can provide valuable customer interactions and bridge online and offline experiences.
This document provides an overview of various consumer markets and segments relevant to kiosks. It includes statistics on the size and growth of key markets like retail, entertainment, hospitality, fast food and grocery. It also analyzes consumer segments within these industries and highlights examples of kiosk applications that have been deployed or tested. The focus is on identifying high-potential market segments and drivers of kiosk adoption across different consumer facing industries.
Craig Keefner runs Kiosks.org, a website dedicated to internet kiosks that provides news, trends, ads, and information to its members. The site serves as a middleman between members and potential customers. It has grown significantly since starting in 1996. Keefner is interested in kiosks from his previous work developing systems for retail kiosks. He now tracks kiosk trends and receives many inquiries about combining kiosks with pay phones. Pay phone providers see potential in using kiosks to provide internet access for phone users.
2. Scope
• Overview
• Technology, Standards, Limitations
• Facial Recognition
• Applications and Advantages
• Is Visionics & Biometrics the Future?
3. Overview
• Visionics is subset of Biometrics
• Biometrics is defined as the use of
anatomical, physiological or
behavioural characteristics to
recognise or verify the claimed
identity of an individual.
4. Overview
• Originally developed for high
security applications.
• Confirms the presence of the
individual rather than a token
5. Technology
• Retinal Scan and Iris Scan
• Fingerprint and Hand Geometry
• Signature and Voice Dynamics
• Facial Recognition
• Vascular Patterns
6. Technology
• Other biometrics systems proposed but never
brought to market - yet. Include the use of
the earlobe, a person’s smell, and a person’s
gait to identify an individual.
• Much work in biometrics research, driven
primarily by the military. DARPA for example,
sponsors much of the research in the US,
with “Human ID at a distance” being one of
their ongoing projects .
7. Technology - Industry
• ~ 150 Biometric Companies
• Veridicom dismantled in August
• 2001: 60%+ growth (post
9/11/01)
10. Technology - Industry
• Harris Interactive (consulting) +9/11
– “82% of Americans are willing to have their
fingerprints scanned for increased airport
security”
– “86% favor facial-recognition technology to
scan for suspected terrorists”
– (CNBC 9/19/01: Alan Dershowitz: “facial
recognition is better than racial profiling”)
11. Technology - Industry
Wall Street Journal 11/13/01
“The Airport of The Future”
“A special scanner scrapped in
Charlotte, N.C., identified people
by their iris but couldn’t detect
guns.”
12. Technology - Standards
• The BioAPI standard is intended to
provide a mechanism where by a
single application can utilise different
biometric approaches. It provides a
standard interface between the
application layer and any biometrics
system that provides BioAPI
compatible drivers or subsystems.
13. Technology - Standards
• Two other standards of note in the
area are the ANSI X9.84 standard,
which is about common templates for
common biometrics devices and the
CBEFF (Common Biometric Exchange
File Format) is trying to establish a
universal file format recognisable to
various applications.
14. Technology - Standards
CBEFF Defined Biometric Type CBEFF Type ID Static/Dynamic Identification
Suitability
Multiple Biometrics Used 0x01 - -
Facial Features 0x02 Static No
Voice 0x04 Dynamic No
Fingerprint 0x08 Static Yes
Iris 0x10 Static Yes
Retina 0x20 Static Yes
Hand Geometry 0x40 Static No
Signature Dynamics 0x80 Dynamic No
Keystroke Dynamics 0x100 Dynamic No
Lip Movement 0x200 Dynamic No
Thermal Face Image 0x400 Static No
Thermal Hand Image 0x800 Static No
Gait 0x1000 Dynamic No
Body Odor 0x2000 Static No
DNA 0x4000 Static Yes
Ear Shape 0x8000 Static No
Finger Geometry 0x010000 Static No
Palm Geometry 0x020000 Static No
Vein patter 0x040000 Static No
15. Technology - Limitations
Biometric Crossover Accuracy
Iris scan 1:10.000,000+
Retinal Scan 1:131,000
Fingerprints 1:500
Hand Geometry 1:500
Signature 1:50
Voice 1:50
Facial no data
Vascular no data
16. Technology - Limitations
Biometric Record Data Size (Bytes)
Retinal Scan 96
Iris Scan 512
Fingerprints 512-1000
Hand Geometry 9
Signature 3900
Voice 60/word
Facial Recognition 100-3500
17. Technology - Limitations
Verification versus Identification
•User base of millions
•Real-time verification precluded
•Token with template possible
•Verify identity against template
18. Technology - Limitations
Transaction/User Base Examples
• In May 2000 there were
over 400,000 transactions at
Exxon and Mobil C-stores.
• For 2002 projects to over
35 million transactions.
• 185,000 ATMs in the US
• Close to 15B transactions in
US in 2002 (declining)
19. Technology - Limitations
Templates - Storage & Processing
•Local to Local - within a smart card
•Local and Terminal - template on
smartcard copied to terminal to be verified.
•Remote and Terminal - template stored
remotely and compared to local template
•Remote and Remote - locally acquired
template is compared on remote system to remote
template.
20. Technology - Limitations
• Failure To Enroll - critical to get good measurement at this stage.
Some will choose not to use the system and must still be processed.
• Failure To Acquire - systems that require high level of user
cooperation.
• False Positive (FAR) - users must trust and accept
• False Negative (FRR) - how many rejected falsely?
• EER (Equal Error Rate Crossover)
21. Technology - Limitations
• False Acceptance Rate (FAR): The chance that an imposter will
be recognized (obtain a higher score) at a certain threshold.
• False Rejection Rate (FRR): The chance that the correct
person will not obtain a score above a certain threshold.
• Both the FAR and FRR are functions of threshold. The
threshold where the two probabilities are the same is the
Equal Error Rate (EER). For example, if the EER is 1%, that
means 1% is the right people are rejected and 1% of the
wrong people are accepted above a certain threshold.
22. Technology - Limitations
• Crossover point between FAR and FRR known as
the Equal Error rate (EER) and this is often
quoted. Argued that the lower this figure is, the
better the system performance is. Unfortunately,
how the figure was established can seriously
affect it. A system that performs well in the
laboratory with trained, co-operative users will
generate a completely different set of values
with inexperienced or less co-operative users.
23. Technology - Limitations
Probability
Distribution
EER
Genuine Imposter
Score
(e.g. hamming distance)
false accept false reject
24. Technology - Limitations
Centre for Mathematics and Scientific Computing National Physical Laboratory Middlesex, UK
“Biometric Product Testing Final Report”
Issue 1.0 March 19, 2001
26. Technology - Limitations
The Most Intriguing - The Iris
Forms during 3rd month of
gestation, 8th month Pattern
complete, coloration through crypts
Iris radial furrows
after birth
Only internal organ of the body
that is normally visible externally pigment frill
Pupil
(highly protected
by cornea and eyelid) pupilary area
Impossibility of surgically ciliary area
modifying it without
Sclera
unacceptable risk to vision collarette
27. Technology - Limitations
The Most Intriguing - The Iris
• Iris verification has been, and still is, used in ATMs
(Bank United in Texas for example). The size and the
cost (>$1000 for an ATM compatible system) seem to
be the main reasons for this system not growing
further in this area. The risk of fraud by the use of
force is possible. The thought of attempting fraud by
mutilation of a user is distasteful but could exist.
28. Technology - Limitations
Other Considerations
• Enrolling Users
• Sheer number of Users
• How invasive?
• How stored and available how?
• Still PIN systems, will users forget?
29. Facial Recognition
• Humans Are Easily Fooled By
Pictures
• Vendors: Visionics, Bio4, Viisage
(Lau), eTrue, Imagis…
• Pros; Least Invasive, Fast
• Issues: lighting, aging… general
error rates
• Existing Database – Usability?
30. Facial Recognition
Methods for Matching
• Automatic face processing.
• Neural Network processing
• Eigenfaces
• Local Feature Analysis.
31. Facial Recognition
• Facial Recognition Vendor Test 2000
(FRVT 2000)
- Sponsors: Counterdrug Tech Prog Office, NIST, DARPA
- Performance Update - State of technology & Specific
Vendors
- Update of FERET 1993-1998
(FacEREcognitionTechnology)
- 13,872 Images of 1462 subjects In nxn Test
(192 Million Comparisons over 72 hrs)
- Results Summarized in 57 Figures
32. Facial Recognition
FRVT 2000 Test Overview
Banque-
Test Visionics Lau C-VIS Miros Tec Bio4
Expression 1 2 3 - - -
Illumination 1 2 3 - - -
Pose 1 2 3 - - -
Media 1 2 3 - - -
Distance 2 1 3 - - -
Temporal 1 2 3 - - -
Resolution 1 2 3 - - -
1-Best, 3-Worst
General Observations
Facial May Not Be Suitable For Exact “Identification”
(needs human)
Best Case Verification EER ~.02
Distribution Not Symmetrical, Use ROC Not EER
34. Facial Accuracy
Processing False Accepts
• Premise: Load Terrorist Picture Database Into System
• Issues: Quality of enrollment pictures
• Impact Assessment
– e.g. Hartfield Airport
• 150M People Year -> ~411,000 / Day
• 2400 Flights / Day
– @ An Optimistic EER of 2%
• 8219 False Accepts
• @ 20 minutes / False Accept -> 2739 manhours / day
• P(8 false accepts | 375 passengers) = 8.6%
35. Facial Vendors
• Visionics
• Miros
• Bio4
• Viisage
• There are many others...
36. Facial Vendors
Visionics
• Fundamental to any face recognition system is the way
in which faces are coded. Visionics FaceIt® uses Local
Feature Analysis (LFA) to represent facial images in
terms of local statistically derived building blocks.
• LFA is a mathematical technique developed by co-
founders of Visionics Corporation, and is based on the
realization that all facial images (for that matter all
complex patterns) can be synthesized from an irreducible
set of building elements.
37. Facial Vendors
Visionics
• They span multiple pixels (but are still local) and
represent universal facial shapes, but are not exactly the
commonly known facial features. In fact, there are many
more facial building elements than there are facial parts.
However, it turns out that synthesizing a given facial
image, to a high degree of precision, requires only a
small subset (12-40 characteristic elements) of the total
available set. Identity is determined not only by which
elements are characteristic, but also by the manner in
which they are geometrically combined (i.e. their relative
positions).
38. Applications & Advantages
Authentication
• Computer/Network Security
• Banking
• Smart Cards
• Access Control
• Border Control
40. Applications & Advantages
Human ID at a Distance
• Surveillance
• CCTV
• Human Traffic Control
• Friend or Foe
41. Applications & Advantages
ID Solutions
• Voter Registration
• National Ids
• Passports
• Drivers Licenses
• Employee IDs
42. Applications & Advantages
ID Examples
• Eliminating Aliases & Duplicates
• Mexican Election System
• West Virginia
• Colorado State DMV (under
installation)
• Dominican Republic
• U.S. State Department Visa
Issuance Program
43. Applications & Advantages
• UK Prime Minister Tony
Blair visits the FaceIt®
Surveillance installation
in Newham, where
crime has been reduced
by 34% overall.
44. Applications & Advantages
• ATMs
• Integrating facial biometrics systems into an
ATM is a real possibility as in many cases the
sensing system (camera) is already there and
could easily be used.
• Persons trying fraud via decapitation of the
legitimate user is gruesome but imaginable.
The use of masks is another avenue for
potential fraud
45. Applications & Advantages
• Facial recognition technology is the only
commercially-available biometric capable
of identifying humans at a distance. It
has already been deployed in some high-
profile locations -- in casinos, European
soccer matches and in town centers --
and has shown significant results.
46. Applications & Advantages
January 14: British Virgin Islands Select
AiT's Automated Border Management
System: $1.1 million contract for enTReX
• At each inspection point, AiT's imPAX Reader will be used
to capture images of travellers ID documents, and digital
cameras will capture live facial images. All of the images
and data captured will be sent to enTReX, a software-
based border management system, for processing. The
system provides better tools to deal with undocumented
travellers, identify those without a legitimate right to be
on the islands, and detect mismatches between those
exiting the border and those who entered.
47. Applications & Advantages
January 4, 2002 CNET
Visionics signed a deal late last year with
conglomerate Tyco International to distribute
its technology at some 100 of the nation's 450
commercial airports. Even the U.S. Army
recently licensed face-recognition technology
from rival Viisage Technology to create custom
high-security applications.
48. Is Visionics the Future?
An industry in search of a compelling mass
application
No clearly appreciated value proposition
(convenience can only go so far)
Several adoption barriers
Privacy concerns
Political will to change
Lack of infrastructure & funding
49. Is Visionics the Future?
Positives
ID technologies: a corner stone of
defense against terrorism & crime
Safety & Security: clear and present
value propositions
Accelerated funding & federal security
mandates
Favorable Public Opinion
50. Is Visionics the Future?
Positives
• Security is no longer viewed as a drag on bottom
line: at least for now.
• WTC disaster will cost NYC an $100 billion.
Investing in security is like buying insurance
• Significant funding for security programs —
federal, state, local & commercial:
– AIP : Aviation Trust Fund is up
– PFC : increased by up to $5 per one way trip
51. Is Visionics the Future?
New Drivers' Licenses Study Underway
• WASHINGTON (AP) - January 8, 2002 --
The government is working with the
states to develop a new generation of
drivers' licenses that could be checked
anywhere and would contain electronically
stored information such as fingerprints for
the country's 184 million licensed drivers.
52. Is Visionics the Future?
Camera May Be Able to Spot Liars
• Minnesota - January 3, 2002 -- A heat-
sensing camera trained on people's faces was able
to detect liars in a study. In six of eight people who
lied, the high-resolution thermal imaging camera
detected a faint blushing around their eyes that
Mayo Clinic researchers said is evidence of
deception. Such facial imaging, they said, could
provide a simple and rapid way of scanning people
being questioned at airports or border crossings.
53. Is Visionics the Future?
Net Nanny Signs International Distributors
For BioPassword
• December 4, 2002 -- Net Nanny Software
International Inc. (OTCBB:NNSWF - news;
CDNX:NNS.V) announced today that it has signed
Wildspace, Ltd., Junek Ltd. and Joint Future
Systems, S.C., which are headquartered in the UK,
Czech Republic and Mexico respectively, to
distribute its strong user authentication
technology, BioPassword®.
54. Is Visionics the Future?
Net Nanny Signs International Distributors
For BioPassword
• All three companies will distribute BioPassword, the
authentication solution for enterprise networks,
and the BioPassword software developer's kit,
which enables third parties to incorporate the
patented keystroke dynamics technology into their
own applications.
56. Is Visionics the Future?
Issues To Deal With
• Privacy -- for verification rather
than identification the issue is
smaller. Orwellian perception.
57. Is Visionics the Future?
ACLU in January 2002 noted:
• "Face recognition is all hype and no action," Barry
Steinhardt, associate director of the ACLU, said in a
statement. "Potentially powerful surveillance systems
like face recognition need to be examined closely
before they are deployed, and the first question to ask
is whether the system will actually improve our safety.
The experience of the Tampa Police Department
confirms that this technology doesn't deliver."
58. Is Visionics the Future?
Conclusions
• Commodity level implementation still 2 to 3
years away.
• Government is the big driver.
• Smartcards, ID Cards, Mobile, Credit Card
are some of the new Driver Enablers
59. Visionics
Personal Thanks and Appreciation for
the Encouragement provided by these
leading companies:
• Symbol Technologies
• NCR Corporation
• Visionics
• Wincor Nixdorf
60. Visionics
Thank You
For More Information
• Visit Kiosks.org Association at www.kiosks.org/smi
• The UK Biometrics Working Group, Biometric Product Testing, Final Report. At
http://www.cesg.gov.uk/technology/biometrics/media/Biometric%20Test%20Report%20pt1.pdf
• Biometric Market Report 2000-2005,
http://www.biometricgroup.com/e/biometric_market_report.htm
• Visionics Corporation http://www.visionics.com/faceit/apps/auth.html
• Neusciences - Biometrics http://www.neusciences.com/Biometrics/applications.htm
• Miros http://www.miros.com/
• Advanced Biometrics Inc. http://www.livegrip.com/
• Iridian http://www.iridiantech.com/
• The Defense Advanced Research Projects Agency (DARPA) Human ID at a Distance
http://www.darpa.mil/ito/research/hid/
61. Visionics - Addendum
Craig Keefner is the Executive Director of Kiosks.org Association. The
Association is worldwide and includes both vendors and users/deployers. It’s
mission is to identify and promote the interests of companies engaged in the
electronic, self-service kiosk industry.
Working committees include: Marketing and Public Relations, Best Practices,
Technology and Standards, Government Relations, Research and Statistics,
Advertising and Developing Markets. The President of the Association is Mr..
Richard Rommel of Eastman Kodak and the Chairman is Mr.. Richard Good of
NetWorld Alliance.
Members include: NCR Corporation, Symbol Technologies, Wincor-Nixdorf, IBM,
Compaq, Intel, Eastman Kodak, MEI, Netshift, Eurocoin, ePOINT and many
many others.
For more information or to join: go online at www.kiosks.org/join or call 1-866-
240-1318. You can email us at info@kiosks.org
This presentation delivered February 6, 2002 at The Hatton for Kiosks 2002