Skip Navigation LinksHome > Technology > AuthenticationTools

                    Authentication Tools

 
  Fingerprint Recognition
  Face Recognition
  Iris Recognition
  Hand Scan
  Voice Recognition
  Fingerprint recognition

Fingerprint biometrics is probably the most common form of biometrics available today. Fingerprints, when scanned electronically, provide greater details and hence higher level of accuracy can be achieved over manual systems. Studies have also found that using fingerprints as an identification source is the least intrusive of all biometric technique. Users experience fewer errors in matching when they use fingerprints as against many other biometric methods. Several companies have produced capture units smaller than a deck of cards. Finger-scan technology is thus the most prominent biometric authentication technology, used by millions of people worldwide. Used for decades in forensic applications, finger-scan technology is steadily gaining acceptance in fields as varied as physical access, network security, service access, e-commerce and retail.
   
 
Face recognition:

Facial scan technology is an increasingly prominent biometric authentication technology, one well suited for a number of applications in which other biometric technologies are simply unusable.
Making use of distinctive features or characteristics of the human face, often irrespective of facial hair or glasses, facial scan is deployed in fields as varied as physical access, surveillance, PC access, and ATM access. Authentication process involves the user entering some identifying information such as a login name or pin, having a snapshot taken in front of the camera and then being verified. It also has the ability to track moving faces. There are four primary methods used to identify and verify users. They include eigenfaces, feature analysis, neural network and automatic face processing. Eigenfaces, which means roughly "one’s own face", is a MIT patented technology, which utilizes two dimensional grayscale images representing distinctive characteristics of a facial image. Neural Network analyses features from both images, the enrollment and verification image and determines if there is a match using an algorithm. Automatic Facial Processing (AFP) uses distances and distance ratios between certain features of the face, namely eyes, end of nose and corner of mouth. It is not as robust as Eigenfaces, but would be more effective in a dimly lit situation.
 
 

Iris recognition


Iris biometrics is exceptionally accurate, especially in environments where the fingerprints are worn out due to hard manual labor. Iris technology is relatively more expensive to use and does take-up slightly more time for the enrollment and authentication process. Iris scanners are typically multi-purpose and incorporate regular video capabilities with the scanner. Iris biometric devices are more accurate than fingerprint because an iris has more characteristics to identify and match than those found on the finger. The error rate for the typical iris scanner is about one in two million attempts, which further demonstrates the reliability of this technology.There are several industries, which are interested in this type of technology, particularly banking & Finance. Banks are incorporating Iris Scanning systems into their ATMs. Some prisons are also using this technology today to identify inmates and guards.

   
 

Hand Scan


Hand-scan is a relatively accurate technology, but does not draw as rich a data set as finger, face, or iris. Hand-scan does not perform one-to-many identification, as similarities between hands are not uncommon. The submission of the biometric is straightforward, and with proper training can be done with little misplacement. The template size of a hand scan is up to 9 bytes which is extremely small compared to most other biometric technologies. By contrast, finger scan biometric requires 250-1000 bytes and voice scan biometric commonly requires 1500-3000 bytes. This facilitates storage of a large number of templates in a standalone device. It also facilitates card-based storage, as even magstripe cards have ample room for 9 byte samples.

   
 

Voice recognition

Voice recognition is "the technology by which sounds, words or phrases spoken by humans are converted into electrical signals, and these signals are transformed into codsing patterns to which meaning has been assigned" The most common approaches to voice recognition can be divided into two classes: "template matching" and "feature analysis". Template matching in voice recognition is the simplest technique and has the highest accuracy when used properly, but it also suffers from the most limitations. As with any approach to voice recognition, the first step is for the user to speak a word or phrase into a microphone, the electrical signal from the microphone is digitized by an "analog-to-digital (A/D) converter", and is stored in memory. To determine the "meaning" of this voice input, the computer attempts to match the input with a digitized voice sample, or template, that has a known meaning.

   
   
     

  FIRST FINGERPRINT BIOMETRIC BASED ATM WITH EFT SWITCH BASED AUTHENTICATION



FIRST PALM-VEIN BIOMETRIC BASED ATM



FIRST RURAL ATM –EXTREMELY LOW POWER (SOLAR), RUGGED, NON-AC USAGE



RETRO-FIT KIT TO INSTANTLY CONVERT REGULAR ATMs TO BIOMETRIC ATMs



BSM – BIOMETRIC SECURITY MODULE- FOR EFT SWITCH



FIRST PASSBOOK PRINTING KIOSK



ABM – AUTOMATED BANKING MACHINE – FULL BANKING INCLUDING CARD PERSONALIZATION WITH PASSPORT, DRIVER LICENSE, NATIONAL ID SCANNING, CASH / COIN MANAGEMENT



CASHLESS ATM



WORLDS SMALLEST FULL-FUNCTIONAL ATM (WALL MOUNTABLE)



ADVANCED INTELLIGENT ATM/SELF-SERVICE TERMINAL MONITORING



LINUX BASED XFS



MOBILE (VEHICLE BASED) ATM



COMPLETE MICRO-FINANCE SOLUTION



BIO-POS



Axis Software Pvt. Ltd.
1215/2/13, K. P. Kulkarni Marg, Off Apte Road, Shivaji Nagar, Pune - 411004,
Maharashtra,INDIA
Tel. +91-20 25530297
Fax. +91-20 25537591/1795


 
© 2008 Axis Software Pvt.Ltd. All Rights Reserved                                                               Best Viewed on Firefox,Google Chrome