Some devices are 'tuned' for certain algorithms, and so enrolling with device A and matching with device B may not work at all despite having picture-perfect fingerprints.

Furthermore, some devices actually return multiple channels of data (various spectrums of light for example) and you have to throw away all but one channel so that the application can remain device agnostic, which is a hard decision.įinally keep this in mind: if you do minutiae extraction, the device you use unfortunately WILL impact which minutiae are detected. ASHATA USB Fingerprint Reader,USB Fingerprint Sensor Optical Fingerprint Scanner, Mini Biometric Fingerprint Reader for Desktop PC Security,Mobile PCs,Custom Applications,Home Office Use. programmable flashing lights), and by abstracting the devices away you lost the ability to access these special abilities.

The main problem with this approach is that a lot of devices these days have various gimmicks (e.g. The image data that comes back has to be decided on in advance so that you know what you're going to get every time Then from the C# side all you have to do is 'pick' a device (all you have to go on is a unique ID and maybe a manufacturer) and then use it. Knowing this, my company wrote a library which initializes and sets up each device, creates a generic wrapper, assigns a unique ID, and throws it into a big list that you can enumerate over. Consider that all fingerprint scanners only REALLY need one call: getImage. My company had to develop a fingerprint device abstraction library for this very reason. Get the latest WHQL certified drivers that works well.I work in the biometric field, and I use C# for a lot of the fingerprint stuff I do. We check all files and test them with antivirus software, so it’s 100% safe to download.

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