Live Finger Detection Technology in India
In India still people are using traditional authentication methods such as locks & keys and PIN, even though the technology has made a giant leap forward in physical security systems. By using the traditional approach we Indians are often compromising our security. Anyone can use duplicate keys by stealing or our PIN code may be shared to others. These problems can be sorted out only with the help of biometric authentication. Biometric Authentication ensures credibility and enhancing security and prevents others from using our credentials.
Fingerprint technology is the most adopted technology in biometric authentication as it offers the most flexibility with reasonable price ie cost benefits. Now days it is used wide range in various applications from mobile devices to banking transactions. Finger print is the most recommended than other biometric technology like iris or face recognition. Finger print technology is suitable for the most aggressive and most populous Indian market with its flexible and reliable method with high recognition rate. The only challenge in using Finger print technology is the usage of fake fingerprints. The fake fingerprints are generated from clay, gelatine and silicone and rubber. Iphone 5s is first to introduce built in fingerprint sensor in order to avoid the spoofing as lot of the IT magazines reported about the fake fingerprints.
Suprema’s Live Finger Detection Technology 2.0
Suprema came out with the Live Finger Detection Technology (2.0), featured with the dynamic and static image characteristics of the fake fingers and how it has been contradicted from live fingers.
Dynamic Changing Pattern
Primarily fingers gradually make contact with the sensor surface, real fingers usually changes in its template recorded with area, intensity and movement but fake fingers produce artificial changes like separated areas or partially dark area, distorted boundary shape and drastic movement on core parts. By using this logic dynamic changes has been observed with the fake and real fingers and also this method give us the very effective resulting in rejecting fake fingers even they are in the hard materials like paper, film, clay and hard rubber.
Real Finger Feature Analysis:
In the real fingerprint template, there are several features which reveal the liveliness of fingers: Pore distribution, ridge sharpness, regularity of ridge valley boundary among others. These real fingers are usually small and elaborate to copied by simple and soft making materials such as silicon, rubber and gelatine. Suprema provide high performance imaging sensor features to capture high quality finger print images. So local liveliness features are easily be distinguished by this algorithm.
Artificial Finger Feature Analysis:
As you know, really it is very hard to make a perfect fake finger and almost every fake finger will have artificial sharp boundaries, many white blobs or too large black bobs in the fingerprint template area. It used to record abnormal peaks in histogram distribution and there is lot. By recording the mixture of many artificial finger features almost all fake fingers are effectively rejected.