Die Zukunft des Bankings ist smart: Die neue App der Deutschen Bank unterstützt eine ganze Reihe neuer, innovativer Technologien, um das Mobile-Banking noch
bequemer zu machen.
So überweisen Kunden zukünftig: Die Deutsche Bank bietet Kunden die Möglichkeit, Bankgeschäfte via „photoTAN“ zu erledigen. photoTAN gilt dabei als modernes und komfortables Sicherheitsverfahren bei Transaktionen. Als besondere Funktion kann sich die photoTAN-App automatisch mit der „Meine Bank“-App verbinden.
Unsere weiteren TWT Trendradare finden Sie hier: http://bit.ly/1MjPpst
Fingerprint recognition system by sagar chand guptascg121433
This document provides an overview of fingerprint recognition systems. It defines biometrics and discusses physiological and behavioral characteristics used for identification, including fingerprints. The history of fingerprint analysis and classification of fingerprint patterns are covered. The document explains that fingerprint recognition systems work by acquiring fingerprints, extracting minutiae features, and matching minutiae between samples. Various fingerprint sensor technologies and applications like banking security and access control are also summarized.
This document discusses fingerprint recognition as a biometric system for identity verification. It describes how fingerprint recognition works, including minutiae extraction to identify ridge endings and bifurcations, and minutiae matching to compare fingerprints. The key steps are minutiae extraction from a scanned fingerprint, and then matching the minutiae of the scanned print to those in a database. Applications include access control, transactions, and forensics. Limitations include fingerprint quality issues and the need for a large database.
Tracko: Asset Tracking and Real Time Locationg Solution Onyx Beacon
Track assets on the go, using Bluetooth beacons & mobile technology. A new generation RTLS solution for logistics & manufacturing professionals & warehouse and factory staff to quickly locate the machines, equipment and inventory they need, within their premises. Without expensive readers & manual scanning/location updates.
Beacons for next-level Banking: 12 functionalities for a Tailored Customer Ex...Onyx Beacon
Bluetooth Beacons installed at financial service branches allow banks to integrate physical and mobile channels, to create a new type of interaction and effective commercial communication and to deliver to the customers a positive, pragmatic and personal experience.
Our integrated mobile solution includes all the components needed to make this experience immediately effective and is ready for complete integration with the bank own CRM and other platforms via API. For privacy and data security reasons, our solution is ready to be deployed as a Virtual Appliance on clients’ premises.
Our integrated solution brings 12 functionalities that seriously upgrade customer experience in banking: Presence Detection, Customer ID Recognition, Welcome Interaction, Desk and Clerk Allocation, Notifying Account Managers, Tailored Financial Offers, Up-Selling and Education, Cross-selling and New Income, Branch Analytics, Satisfaction Surveys, Mobile Payments and Contextual Advertising.
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.
So überweisen Kunden zukünftig: Die Deutsche Bank bietet Kunden die Möglichkeit, Bankgeschäfte via „photoTAN“ zu erledigen. photoTAN gilt dabei als modernes und komfortables Sicherheitsverfahren bei Transaktionen. Als besondere Funktion kann sich die photoTAN-App automatisch mit der „Meine Bank“-App verbinden.
Unsere weiteren TWT Trendradare finden Sie hier: http://bit.ly/1MjPpst
Fingerprint recognition system by sagar chand guptascg121433
This document provides an overview of fingerprint recognition systems. It defines biometrics and discusses physiological and behavioral characteristics used for identification, including fingerprints. The history of fingerprint analysis and classification of fingerprint patterns are covered. The document explains that fingerprint recognition systems work by acquiring fingerprints, extracting minutiae features, and matching minutiae between samples. Various fingerprint sensor technologies and applications like banking security and access control are also summarized.
This document discusses fingerprint recognition as a biometric system for identity verification. It describes how fingerprint recognition works, including minutiae extraction to identify ridge endings and bifurcations, and minutiae matching to compare fingerprints. The key steps are minutiae extraction from a scanned fingerprint, and then matching the minutiae of the scanned print to those in a database. Applications include access control, transactions, and forensics. Limitations include fingerprint quality issues and the need for a large database.
Tracko: Asset Tracking and Real Time Locationg Solution Onyx Beacon
Track assets on the go, using Bluetooth beacons & mobile technology. A new generation RTLS solution for logistics & manufacturing professionals & warehouse and factory staff to quickly locate the machines, equipment and inventory they need, within their premises. Without expensive readers & manual scanning/location updates.
Beacons for next-level Banking: 12 functionalities for a Tailored Customer Ex...Onyx Beacon
Bluetooth Beacons installed at financial service branches allow banks to integrate physical and mobile channels, to create a new type of interaction and effective commercial communication and to deliver to the customers a positive, pragmatic and personal experience.
Our integrated mobile solution includes all the components needed to make this experience immediately effective and is ready for complete integration with the bank own CRM and other platforms via API. For privacy and data security reasons, our solution is ready to be deployed as a Virtual Appliance on clients’ premises.
Our integrated solution brings 12 functionalities that seriously upgrade customer experience in banking: Presence Detection, Customer ID Recognition, Welcome Interaction, Desk and Clerk Allocation, Notifying Account Managers, Tailored Financial Offers, Up-Selling and Education, Cross-selling and New Income, Branch Analytics, Satisfaction Surveys, Mobile Payments and Contextual Advertising.
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.
Fingerprints are unique and can be used to identify individuals. They are comprised of ridges and valleys that form distinctive patterns classified as loops, whorls, or arches. Fingerprint identification involves comparing ridge characteristics like ending ridges, bifurcations, and dots between two prints and looking for multiple matching characteristics in the same relative positions to determine a match. While some countries have a set number of ridge characteristics required for identification, examiners in the US can use their experience and discretion to decide based on print clarity and uniqueness.
Fingerprint recognition is a biometric technique that uses fingerprint patterns to identify or verify individuals. It works by extracting minutiae points like ridge endings and bifurcations from scanned fingerprints and matching them against a database. The process involves fingerprint acquisition using optical or semiconductor sensors, minutiae extraction after preprocessing and thinning the image, and minutiae matching for verification or identification. Fingerprint recognition has applications in security systems and has advantages of high accuracy and small storage requirements, though it can be affected by dirty or wounded fingers.
Detection and rectification of distorted fingerprintJayakrishnan U
This document discusses challenges in fingerprint recognition related to low quality fingerprints and distortions. It summarizes approaches to detect distorted fingerprints and rectify them for fingerprint matching. The key approaches discussed are:
1. Detecting distortions by analyzing registered ridge orientation and period maps of fingerprints as feature vectors.
2. Rectifying distortions by searching a reference database of distorted fingerprints to find the nearest neighbor and corresponding distortion field to inverse transform the input fingerprint.
3. Evaluating these approaches on benchmark datasets shows improved detection of distorted fingerprints and higher matching accuracy after rectification compared to previous methods.
This document provides an overview of fingerprint recognition technology (FRT). It begins with definitions of biometrics and FRT. It then discusses the history of fingerprint analysis and why fingerprints are used for identification. The document describes different fingerprint sensing technologies including optical, silicon-based capacitive, ultrasound, thermal, and piezoelectric sensors. It also covers fingerprint feature extraction, matching, storage and compression, challenges of variability, and applications of FRT. The presentation concludes with emerging 3D fingerprint technologies and references for further information.
This document summarizes a student project on fingerprint recognition. The project involved implementing a fingerprint recognition algorithm using minutia extraction and matching. The algorithm included preprocessing stages like histogram equalization, Fourier enhancement, binarization, and thinning. Minutiae were then extracted and matched to determine if two fingerprints came from the same finger. The results showed the algorithm could accurately match fingerprints from the same finger but determine fingerprints from different fingers did not match.
This document describes a fingerprint-based ATM and locker system for modern secured banks. The system uses fingerprint biometrics for authentication. It includes a fingerprint scanner, microcontroller, LCD display, buzzer, keypad, EEPROM, and connections to an ATM and locker. The fingerprint is scanned and matched to stored templates to authenticate users for bank transactions or locker access. The system is intended to provide secure authentication as fingerprints cannot be forgotten, stolen, copied or used by others like cards or passwords.
Fingerprints have been used for identification since 1882. There are three main fingerprint patterns: loops, whorls, and arches. Loops make up 65% of fingerprints, whorls 30%, and arches 5%. Fingerprints are identified by features called minutiae including bifurcations, endings, and cores. There are two main techniques for fingerprint matching: minutiae-based which matches placement of minutiae points, and correlation-based which can overcome difficulties of minutiae-based matching. Fingerprints are captured using either optical or capacitive sensors and processed using image algorithms. Fingerprint identification has advantages of high accuracy, economy, and standardization but disadvantages of potential intrusiveness and errors from dirty or
Digitalisierung in der öffentlichen Verwaltung mit dem „digitalen Amt“ - oesterreich.gv.at als Plattform für Mobile Government - MR Ing. Roland Ledinger (Bundesministerium für Digitalisierung und Wirtschaftsstandort).
E-Payment Armband für Händler & Kunden
Auf der Konferenz DLD 2015 hat der Payment-Experte Wirecard ein Armband präsentiert, mit dem man am PoS nahtlos zahlen kann.
TWT Trendradar: Mit der WeChat mobile Wallet im Facebook Messenger bezahlenTWT
Die Chinesische App WeChat, die ca. 500 Millionen Nutzer hat, verfügt über eine Wallet mit integriertem mobilen Paymentservice. Finanztransaktionen von Nutzer zu Nutzer sind ebenfalls möglich.
Außerdem kann der Kauf von Kino-Karten, Bahntickets und Taxibestellungen über die Wallet abgewickelt werden. In einer weiteren Funktion, dem WeChat Store, wird sogar im Facebook- Messenger ein Online Shop erstellt. Durch Flash-Sales und Coupons wird Interesse geweckt.
HR Ing. Roland Ledinger (Bundesministerium für Digitalisierung und Wirtschaft...Agenda Europe 2035
Das digitale Amt - oesterreich.gv.at als Plattform für Mobile Government. HR Ing. Roland Ledinger (Bundesministerium für Digitalisierung und Wirtschaftsstandort).
Lokalen Content über iBeacons anbieten:
Ein britisches Unternehmen möchte Apples iBeacons nutzen, um Fachzeitschriften lokal an bestimmten Orten verfügbar zu machen. Wir beleuchten den Trend.
Diese Präsentation befasst sich mit den Anforderungen des mobile Web an die Unternehmenskommunikation. Themen sind Mobilisierung von Websites, Apps, QR Codes etc.
Fingerprints are unique and can be used to identify individuals. They are comprised of ridges and valleys that form distinctive patterns classified as loops, whorls, or arches. Fingerprint identification involves comparing ridge characteristics like ending ridges, bifurcations, and dots between two prints and looking for multiple matching characteristics in the same relative positions to determine a match. While some countries have a set number of ridge characteristics required for identification, examiners in the US can use their experience and discretion to decide based on print clarity and uniqueness.
Fingerprint recognition is a biometric technique that uses fingerprint patterns to identify or verify individuals. It works by extracting minutiae points like ridge endings and bifurcations from scanned fingerprints and matching them against a database. The process involves fingerprint acquisition using optical or semiconductor sensors, minutiae extraction after preprocessing and thinning the image, and minutiae matching for verification or identification. Fingerprint recognition has applications in security systems and has advantages of high accuracy and small storage requirements, though it can be affected by dirty or wounded fingers.
Detection and rectification of distorted fingerprintJayakrishnan U
This document discusses challenges in fingerprint recognition related to low quality fingerprints and distortions. It summarizes approaches to detect distorted fingerprints and rectify them for fingerprint matching. The key approaches discussed are:
1. Detecting distortions by analyzing registered ridge orientation and period maps of fingerprints as feature vectors.
2. Rectifying distortions by searching a reference database of distorted fingerprints to find the nearest neighbor and corresponding distortion field to inverse transform the input fingerprint.
3. Evaluating these approaches on benchmark datasets shows improved detection of distorted fingerprints and higher matching accuracy after rectification compared to previous methods.
This document provides an overview of fingerprint recognition technology (FRT). It begins with definitions of biometrics and FRT. It then discusses the history of fingerprint analysis and why fingerprints are used for identification. The document describes different fingerprint sensing technologies including optical, silicon-based capacitive, ultrasound, thermal, and piezoelectric sensors. It also covers fingerprint feature extraction, matching, storage and compression, challenges of variability, and applications of FRT. The presentation concludes with emerging 3D fingerprint technologies and references for further information.
This document summarizes a student project on fingerprint recognition. The project involved implementing a fingerprint recognition algorithm using minutia extraction and matching. The algorithm included preprocessing stages like histogram equalization, Fourier enhancement, binarization, and thinning. Minutiae were then extracted and matched to determine if two fingerprints came from the same finger. The results showed the algorithm could accurately match fingerprints from the same finger but determine fingerprints from different fingers did not match.
This document describes a fingerprint-based ATM and locker system for modern secured banks. The system uses fingerprint biometrics for authentication. It includes a fingerprint scanner, microcontroller, LCD display, buzzer, keypad, EEPROM, and connections to an ATM and locker. The fingerprint is scanned and matched to stored templates to authenticate users for bank transactions or locker access. The system is intended to provide secure authentication as fingerprints cannot be forgotten, stolen, copied or used by others like cards or passwords.
Fingerprints have been used for identification since 1882. There are three main fingerprint patterns: loops, whorls, and arches. Loops make up 65% of fingerprints, whorls 30%, and arches 5%. Fingerprints are identified by features called minutiae including bifurcations, endings, and cores. There are two main techniques for fingerprint matching: minutiae-based which matches placement of minutiae points, and correlation-based which can overcome difficulties of minutiae-based matching. Fingerprints are captured using either optical or capacitive sensors and processed using image algorithms. Fingerprint identification has advantages of high accuracy, economy, and standardization but disadvantages of potential intrusiveness and errors from dirty or
Digitalisierung in der öffentlichen Verwaltung mit dem „digitalen Amt“ - oesterreich.gv.at als Plattform für Mobile Government - MR Ing. Roland Ledinger (Bundesministerium für Digitalisierung und Wirtschaftsstandort).
E-Payment Armband für Händler & Kunden
Auf der Konferenz DLD 2015 hat der Payment-Experte Wirecard ein Armband präsentiert, mit dem man am PoS nahtlos zahlen kann.
TWT Trendradar: Mit der WeChat mobile Wallet im Facebook Messenger bezahlenTWT
Die Chinesische App WeChat, die ca. 500 Millionen Nutzer hat, verfügt über eine Wallet mit integriertem mobilen Paymentservice. Finanztransaktionen von Nutzer zu Nutzer sind ebenfalls möglich.
Außerdem kann der Kauf von Kino-Karten, Bahntickets und Taxibestellungen über die Wallet abgewickelt werden. In einer weiteren Funktion, dem WeChat Store, wird sogar im Facebook- Messenger ein Online Shop erstellt. Durch Flash-Sales und Coupons wird Interesse geweckt.
HR Ing. Roland Ledinger (Bundesministerium für Digitalisierung und Wirtschaft...Agenda Europe 2035
Das digitale Amt - oesterreich.gv.at als Plattform für Mobile Government. HR Ing. Roland Ledinger (Bundesministerium für Digitalisierung und Wirtschaftsstandort).
Lokalen Content über iBeacons anbieten:
Ein britisches Unternehmen möchte Apples iBeacons nutzen, um Fachzeitschriften lokal an bestimmten Orten verfügbar zu machen. Wir beleuchten den Trend.
Diese Präsentation befasst sich mit den Anforderungen des mobile Web an die Unternehmenskommunikation. Themen sind Mobilisierung von Websites, Apps, QR Codes etc.
Vortrag auf den Kundentagen der VR NetWorld GmbH. Diese Folien sollten Fragen aufwerfen. Was wird aus den Banken? Werden wir bald alle mobil bezahlen? Was wird aus den schönen Filialen? Und was können Filial- oder auch Multikanalbanken tun?