Dr. Mohamed Khairy Shahin
INTERNATIONAL JOURNAL OF BIOMEDICAL SCIENCES VOLUME 2 NUMBER 3 2007 ISSN 1306-1216
Biometric Authentication Using Fast
Correlation of Near Infrared Hand Vein Patterns
Mohamed Shahin, Ahmed Badawi, and Mohamed Kamel
behavioral categories. Common physiological biometrics include face, eye (retina or iris), finger (fingertip, thumb, finger length or pattern), palm (print or topography), and geometry, back of the hand vein pattern or thermal images.
Behavioral biometrics includes voiceprints, handwritten signatures, and keystroke/signature dynamics.
Personal verification has become an important and highdemand technique for security access systems in the last decade. Shape of the subcutaneous vascular tree of the back of the hand contains information that is capable of authenticating the identity of an individual [1-5, 22] to a reasonable accuracy for automatic personal authentication purposes. The shape of the finger vein patterns and its use for identification purpose was proposed by Miura et al. [4]. The infrared region is of special advantage since the skin tissue is relatively transparent and the blood absorbs infrared light well. Hence, the veinsbackground contrast is higher than the visible area. Since the arrival of fairly low cost CCD cameras and computer power, it seems straightforward to try to consider these technologies [67]. Normally, black and white CCD cameras are also sensitive in the near infrared region, so a filter blocking the visible light is all that is needed on the camera. Proper lighting is of course essential to obtain even illumination on the skin surface. There are many research attempts for the extraction, segmentation and tracing of subcutaneous peripheral venous patterns [8-11], its main aim is to make data reduction and noise suppression for good diagnostic purposes and for making some quantitative measurements like lengths and diameters for the extracted vessel segments. These techniques are based on
Biometric Authentication Using Fast
Correlation of Near Infrared Hand Vein Patterns
Mohamed Shahin, Ahmed Badawi, and Mohamed Kamel
behavioral categories. Common physiological biometrics include face, eye (retina or iris), finger (fingertip, thumb, finger length or pattern), palm (print or topography), and geometry, back of the hand vein pattern or thermal images.
Behavioral biometrics includes voiceprints, handwritten signatures, and keystroke/signature dynamics.
Personal verification has become an important and highdemand technique for security access systems in the last decade. Shape of the subcutaneous vascular tree of the back of the hand contains information that is capable of authenticating the identity of an individual [1-5, 22] to a reasonable accuracy for automatic personal authentication purposes. The shape of the finger vein patterns and its use for identification purpose was proposed by Miura et al. [4]. The infrared region is of special advantage since the skin tissue is relatively transparent and the blood absorbs infrared light well. Hence, the veinsbackground contrast is higher than the visible area. Since the arrival of fairly low cost CCD cameras and computer power, it seems straightforward to try to consider these technologies [67]. Normally, black and white CCD cameras are also sensitive in the near infrared region, so a filter blocking the visible light is all that is needed on the camera. Proper lighting is of course essential to obtain even illumination on the skin surface. There are many research attempts for the extraction, segmentation and tracing of subcutaneous peripheral venous patterns [8-11], its main aim is to make data reduction and noise suppression for good diagnostic purposes and for making some quantitative measurements like lengths and diameters for the extracted vessel segments. These techniques are based on
References: 194-203, 2004. International Conference of the IEEE/EMBS, Chicago, Oct. 1997.