Before storing the acquired skeleton pattern in memory as matching data, the data volume is compressed to about a 1/10. I can't reveal details, but characteristics are extracted from the skeleton pattern.
Because of its small size, the matching data do not have to be stored in, for example, an external server. The data volume is small enough to be stored in a FeliCa card or a SIM (subscriber identity module) card, not to mention a mobile device.
So, matching data can be kept in a mobile device. To authenticate an individual, the skeleton pattern is restored from the matching data in a mobile device and compared with another skeleton pattern taken from a finger placed on the sensor.
Matching data is, of course, encoded when being stored. Users can select an encryption technology. DES, AES and Sony's "Clefia" can be used.
Basically, a ball of a finger has to be directed at the CMOS sensor. But a vein pattern can be recognized even if the finger is not placed with much care. If, by chance, the vein pattern cannot be recognized due to wrong positioning, all you need to do is to adjust the position of the finger. In case the finger is not correctly placed, three kinds of finger vein patterns are stored as matching data.
Q: What kinds of applications do you have in mind?
Sony: Let me explain it using its adoption to a PC as an example. First, mofiria can be used for logging on to a PC. When a PC is used by more than one person, it is possible to switch between users by holding their fingers over the sensor.
Also, each finger can be associated with an application. For example, the browser starts with the index finger, presentation software is launched with the middle finger and the display jumps to an Internet shopping site with the ring finger. User verification at shopping sites can be done using finger veins as well.
Q: When mofiria is actually incorporated in a mobile device, what kind of system structure it will take?
Sony: It varies as required specifications change from device to device. We have to change various parameters such as the distance between the CMOS sensor and LEDs, their angles and the number of LEDs.
As authentication is executed by a processor in a mobile device and matching data is stored in its memory, we just need to add LEDs and a CMOS sensor. And it is possible to enhance the level of security by using a dedicated LSI and memory for authentication.
We will discuss with our clients how to develop the system for commercialization. Our goal is to make it not stand out like a fingerprint authentication system so that it can be more easily employed for consumer products.
If such a highly secure technology as vein authentication can be introduced to mobile phones, users will be able to store more important information in their mobile phones. The greater number of fingers that need to be verified, the higher level of security can be ensured.