Biometric recognition
Biometrics is a collection of methods for uniquely recognizing humans based upon one or more intrinsic physical traits. Facial, voice, fingerprint and/ or iris recognition are just among the most promising techniques in a field developing quickly.
Today, biometric recognition has become a robust, effective and competitive way for personal identification and access control. In the USA, Germany, UK, Japan, and other countries is used by police and immigration departments. But private companies can also use to control access of personnel to restricted areas or use computers or other machines.
Biometric recognition systems have strong advantages. ID cards, passports, keys and transponders can be forgotten, damaged or stolen. Passwords can be forgotten, copied, etc. But you will always have your face, voice and fingers with you, isn't it? The widespread idea that biometrics recognition is unreliable belongs to the past: current systems offer FMR (False Match Rates) and FAR (False Acceptance Rates) close to 1/1000. Combined multiple systems (face-voice-palm-finger-iris) offer DNA accuracy levels.
Fingerprint recognition
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Fingerprint recognition has already a long history. Digital recognition inherits their robustness, easy implementation and general acceptance. Fingerprint digital images, after processing, can take much more details and precise measurements than their ink-and-paper counterparts, thus improving the acceptance rates. Fingerprint recognition systems are employed in:
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NITGEN Fingerprint Identification Modules (FIM)
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FIM Module Series is a stand-alone fingerprint identification module composed of optic sensor and processing board. With a high speed ARM9 CPU and optimized fingerprint algorithm, the FIM module series boasts high identification rate and supports high speed 1:N identification, uploadability and downloadability of data, providing optimal condition for application to access control system, door-lock, etc. FIM module series has functions of fingerprint enrolment, identification,. partial and entire deletion and reset in a single board. It does not require connection with a separate PC, thereby offering a convenient development environment. |
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| FIM 2030 | FIM 2040 | FIM 2060 |
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| CPU | ARM9 200 MHz | Programmable I/O | 3 x I / 2 x O |
| Flash Memory | 1 MB / 4 MB | Log capacity | 8000 events |
| EER | < 0,1% | Sensor type | optical |
| 1:1 Verification time | < 0,8 s | Sensor area | 13 x 15 mm |
| 1:N Identification time | <0,9 s (2000 templates) | Resolution | 500 dpi |
| Template size | 400 bytes | Board dimensions | 93 x 43 mm |
| Template capacity | 8000 | Supply voltage | 5 V |
| Communication | 2 x RS232 |
| FIM 3030 | FIM 3040 | FIM 3060 |
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| CPU | DSP 400 MHz | Programmable I/O | 3 x I / 2 x O |
| Flash Memory | 1 MB | Log capacity | 2000 events |
| EER | < 0,1% | Sensor type | optical |
| 1:1 Verification time | < 0,8 s | Sensor area | 13 x 15 mm |
| 1:N Identification time | <0,8 s (200 templates) | Resolution | 500 dpi |
| Template size | 400 bytes | Board dimensions | 60 x 43 mm |
| Template capacity | 200 | Supply voltage | 3v3 / 5V |
| Communication | 1 x RS232 |
Iris recognition
Iris recognition uses a digital camera plus a subtle infrared illumination to reduce light reflection from the convex cornea, and create images of the intricate detail-rich structures of the iris. Then, digital templates are obtained, providing mathematical representations of the iris yielding unambiguous positive identification of an individual.