this paper, presented a robust method for finger vein recognition with gray level co- occurrence matrix based on the discrete wavelet transform. In first step for compression of the image we used wavelet Daubechies 4. Also we used local binary pattern for feature extraction.The combination of local binary pattern and gray level co- occurrence matrix with discrete wavelet transform is not used before for finger vein recognition. The simulation results show that this method is robust and fast for feature extraction and classification.
INTRODUCTION:
Biometrics is identifying humans by their physiological, behavioral and biological characteristics. Biometrics can be divided into two categories: physiological biometrics and behavioral biometrics. Physiological biometrics are those which recognize individuals from physiological or biological attributes like face, iris, fingerprint, finger vein, hand geometry, etc. Behavioral biometrics on the other hand, are those which recognize individuals from human attitudes such as hand writing, signature or voice recognition. Fig. 1, illustrate enrollment to and authentication with the biometric system.
A general framework of vein recognition is shown in fig. 2. For the feature extraction step of the finger-vein recognition, which is the most important step, popular methods such as Line Tracking (LT), Maximum Curvature (MC) and Wide Line Detector (WL) are used in the literature. Among these, the LT method is very slow in the feature extraction phase. Moreover, LT, MC and WL methods are susceptible to rotation, translation and noise.
Devices for Finger-vein Image Acquisition
Finger-vein biometric systems use infrared (IR) light to capture blood vessels, however, the position of infrared light source affects the quality of the images. Moreover, the image acquisition device should be small and cheap, and it should provide high resolution images. In captured images, the veins appear as gray patterns. As can be seen in Figure 3 finger is placed between the Infrared Light Emitting Diodes (IR-LEDs) and imaging device
Advantages and Disadvantages
1. Internal nature: Vein patterns are inside the skin and cannot be seen by naked eye, therefore, damaged skin will not reduce the chance of finding veins behind the skin. Furthermore, dry, wet or dirty hands would not affect the system.
2. Duplicate protection: Vein patterns are difficult to copy because blood needs to flow during image capturing. Scientists in Hitachi proved that it is impossible to cut the finger and register it to the system because blood will seep out.
