01-05-2013, 02:22 PM
Implementation of Hand Vein Structure Authentication Based System
Implementation of Hand Vein.pdf (Size: 916.25 KB / Downloads: 40)
Abstract
Biometric authentication provides a high security
and reliable approach to be used in security access system.
However, this authentication method has not been widely
implemented in a resource-constrained embedded system. In
this project, we investigate a method of personal
authentication based on infrared vein pattern in the back of
the hand. A biometric feature is extracted from the vein
pattern image and create database .The current image
matched with the database and identify that personal is
authenticate or not. In this project the algorithm consists of
four modules: image capturing, image pre-processing, feature
extraction, and the authentication module. Attach the IR
web camera to the door , automatically when any person open
the door camera will capture the back hand vein of images
,using hough threshold method draw the circle on the vein
and attaching all the center of the circle and get thinning
images, which is use to reduce the error segmentation
problem .Then Minutiae feature extraction include different
point. Housdroff Distance is technique measuring of two
images .If that image is match then only the door is open
otherwise it not. This system directly recognizes the shapes of
the vein pattern by ensuring their Line-Segment Hausdorff
Distance.
Introduction:
A biometric feature provides a high
security access system. Traditional method uses
PIN number, password, key, and etc to identify a
person is unreliable and provide a low level
security. It provides more reliable feature than
the password based authentication system as
biometric characteristic cannot be lost or
forgotten, biometric feature are difficult to
replicate, and require the person to be present for
the authentication process.
Image Pre-Processing Module
As illustrated in Figure, the raw vein image
captured from the camera will be enhanced
through several image pre-processing stages
before the minutiae feature extraction can be
done. This section will discuss on each sub
image pre-processing modules.
Color to Grayscale and jpeg to bmp
Conversion:
By converting the color image to grayscale
image, the image size can be reduced from 24
bits per pixel (colored image) to 8 bits per pixel
(grayscale image). The conversion from jpeg
format to bmp format is necessary because
manipulating images in bmp format is much
easier than it is in the jpeg format. Figure 2
shows the resulting image.
Image Capturing Module
An array of infrared light-emitting diode (LED)
and a thermal camera modified from a webcam
was used to capture the vein pattern in our
system. By illuminate the infrared light beam at
the backside of the hand, the vein pattern in the
back of the hand can be captured using a
modified webcam with an attached IR filter. In
the resulting images, as hemoglobin in the blood
absorbs the infrared light, the vein patterns
captured as shadow and appear darker. Figure
illustrates example of infrared vein image in the
back hand captured in our system.
Histogram Equalization (Contrast
Correction):
The vein image captured is having a low contrast
which the vein pattern is not clearly distinguished
from the surrounding parts. This
is overcome by applying histogram equalization to
the vein image to improve the contrast. Histogram
equalization uses the original image’s histogram and
transforms it to have an equalized histogram.
Equalization of the histogram causes a histogram
with a mountain group closely together to “spread
out” into a flat or equalized histogram. This makes
the dark pixels appear darker and light pixels appear
lighter.
Feature Extraction Module
The feature extraction technique utilizes
the minutiae features extracted from the vein
patterns for recognition as proposed by Lingyu
Wang, Graham Leedham , and David Siu-
Yeung Cho . The minutiae points include
bifurcation points and ending points. Similar to
fingerprints, these feature points are used as a
geometric representation of the shape of vein
patterns.