In the field of biometric recognition, convenience and security of the system are highly demanded. A large database usually leads to long response time and high computational complexity. This work, a new method, is presented to extract the vein patterns from near-infrared images, which are enhanced through the directional wavelet transform and the eight-directional neighborhood methods to further reduce the required computational cost as well as to preserve key information from low-resolution images. In addition, the region of interest of the finger-vein is also robustly located with the physiological properties of a human finger. As a result, a database composed of 340 images was employed to generate the required training and testing of vein geometrical features, that the proposed system can yield real-time requirement by achieving 0% false accept rate, 0.25% false reject rate, and recognition rate up to 100%. Meanwhile, the response time is 300 μs, and thus the proposed algorithm is a very effective candidate for a personal identification system.