Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/48816
Title: Hand vein pattern recognition
Authors: Nguyen, Canh Lich.
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Issue Date: 2012
Abstract: For authentication technologies such as password, keys or cards, all that known during the authenticating process is that the correct information presented to the system, not who is holding it. Any unauthorized person can bypass the security system if possesses or known the information. That issue raises a demand for higher reliable security system. Biometrics system, on the other hand, is automated recognition of individual based on their biological or behavior characteristics. Unique human characteristic such as fingerprint, iris, voice, hand geometry and many are used to verify an identity. Thus in most case, only the authorized person holds the correct information is to be authenticated. This project studies methods for identification using hand vein patterns as a biometric feature. The identification system consists of three modules: vein acquisition, feature extraction and feature identification. Vein acquisition is the process of capturing the blood vessel using some thermal scopes. Though there are many techniques, the near infrared (NIR) and far infrared (FIR) was used. While the first two steps have been previously done in the earlier research, this project focuses on experiments in the feature identification modules. All experiments in this project were carried with some modification to a previous implemented biometric system for Palmprint recognition. In overall, the experiments provide an effective solution for the capability of using a Palmprint Identification System that has been implemented for hand vein recognition purpose.
URI: http://hdl.handle.net/10356/48816
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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