29
MANAGEMENT SOFTWARE
The management software enables the current user to lock/unlock his/her personal computer.
When a user leaves his/her computer, he/she may want to use the software to lock his/her computer. When he/she comes back and wants to unlock the computer, he/she needs to put his/her finger which was used in enrolment into the vein scanner. The software will check if the vein of that finger is matched to the current user or not. If the vein is matched, the computer is unlocked. Like enrolment software, the management software has to deal with MatLab, camera, database and locking/unlocking the system. The below figure shows the flow chart of the software:
Figure 35 Management software flowchart
Modules for dealing with Matlab, camera and database have been referred in the Enrolment software part. In order to lock/unlock the system in Windows XP, the below code is applied.
Lock/unlock keyboard/mouse in Windows XP
The below code illustrates how to disable input from keyboard/mouse in Windows XP (13):
Imports System.Windows.Forms
Public Class WinControl
' This is the function used in order to block the keyboard and mouse:
Declare Function BlockInput Lib "User32" _ (ByVal fBlockIt As Boolean) As Boolean
Private Sub WaitThread(Byval _seconds as integer)
BlockInput(True)
MANAGEMENT
When management software is run, an icon will appear in the system tray (figure 36). If we right-click on the icon a menu will show up with five options:
Lock computer: computer will be locked if this is opted.
Show control panel: if this one is chosen, a popup window will appear for user to observe what are happening.
Launch Enrollment: used to launch the enrolment software
Exit
Figure 36 Management software
When the computer is locked, a black screen will appear with a blink message (figure 37a). In this state, inputs from keyboard/mouse are disabled. In order to unlock the computer, the user put his/her finger which was used in enrolment into the scanner device. The software will extract the vein pattern and compare to patterns in the database. If the pattern is matched, keyboard and mouse are re-enabled.
MANAGEMENT
31 (a) Computer is locked (b)Vein matched, the computer is unlocked
Figure 37
The control panel shows extracted vein pattern, ratios 𝐶
𝐹 and 𝐷
𝐹.
Figure 38 Management control panel
CONCLUSION
32
CONCLUSION
The final product has worked and satisfied individual identification by finger veins applied in personal computer as proposed. The product has been tested with 10 people and worked properly with 8 people. This accuracy is not high mainly due to poor quality of vein images coming in from the camera. This can be improved by using a better near-infrared source and a more sensitive camera. The arrangement of infrared LEDs can also be changed so that we can have different designs of the vein scanner.
The project has demonstrated and proved the capability of personal identification based on vein patterns. Although the scale is small, other applications can be extended by solutions which are used in this project. For large applications, some modules should be done in hardware in order to improve the speed of the whole system. If problems of accuracy and speed are solved there is a huge market waiting for the system such as ATMs, cars, houses, cell phones, entrance doors, etc.
33 response. A. Hoover, V. Kouznetsova, and M. Goldbaum. 3, s.l. : IEEE Tras. Med. Imaging, 2000, Vol. 19, pp. pp 203-210.
3. Multiscale Feature of Finger-Vein Patterns Based on Curvelets and Local Interconnection Structure Neutral Network. Zhongbo Zhang, Siliang Ma, Xiao Han. Changchun : The 18th International Conference on Pattern Recognition (ICPR '06), 2006. 0-7695-2521-0/06.
4. Roy, Divakar. Auto Contrast. Matlab Central. [Online] MatWork. [Cited: 04 04 2008.]
http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=10566&objectType
=file.
5. Rafael C. Gonzalez, Steven L. Eddins, Richard E. Woods. Digital Image Processing Using Matlab. Tennessee, US : s.n.
6. Automatic segmentation and registration of retinal fluorescein angiograpies - Application to diabetic retinopathy. T. Walter, J. Klein, P. Massin, and F. Zana. Copenhagen, Denmark : s.n., May 200. Vol. First international Workshop on Computer Assisted Fundus Image Analysis, pp.
pp 15-20.
7. Perceptual organization of thin networks with active contour functions applied to medical and aerial images. P. Montesinos and L. Alquier. Veinne, Autriche : ICPR'96, 1996. pp. pp 647-651.
8. Direct gray-scale minutiae detection in fingerprints. D. Maio and D. Maltoni. s.l. : IEEE Trans. Pattern Anal. Mach. Intell., Jan 1997. Vol. 19, pp. 27-40.
9. An extraction of finger vein patterns based on multipoint interative line tracing. N. Miura, A.
Nagasaka and T.Miyatake. 2001. Proc. IEICE. Gen. Conf. 2001.
10. Extraction of finger-vein patterns using maximum curvature points in image profile. N.
Miura, A. Nagasaka, and T. Miyatake. 8, s.l. : IEICE TRANS. INF. & SYST, August 2007, Vols.
E90-D.
11. Nagao, M. Methods of image pattern recognition. s.l. : Corona publishing, 1983.
12. Lee, Wei-Meng. Tech your old webcam new tricks : Use video captures in your .NET application. DEVX. [Online] [Cited: 16 Apr 2008.]
http://www.devx.com/dotnet/Article/30375/1763/page/1.
13. Optical trans-body imaging: feasibility of optical CT and functional imaging of living body.
Shimizu, K. 1992, Jpn of Medicina Philosophica 11, pp. 620-629.
34
14. ELJ810-248B — EPIGAP — IR EMITTER, JUMBO, 40DEG. Farnell UK. [Online] Farnell.
[Cited: 02 04 2008.] http://uk.farnell.com/1200326/optoelectronics/product.us0?sku=EPIGAP-ELJ810-248B.
15. Limited, Instrument Plastic. Optolite IR Infrared Filter. Farnell. [Online] [Cited: 04 04 2008.] http://www.farnell.com/datasheets/7749.pdf.
16. Image histogram. Wikipedia. [Online] Wikimedia, 17 01 2008. [Cited: 04 04 2008.]
http://en.wikipedia.org/wiki/Image_histogram.
17. Reeve, Kit. Digital correlation. s.l. : University of Plymouth portal.
18. Sha, Zahra A. How to link Matlab to VB ? DSPRelated.com. [Online]
http://www.dsprelated.com/groups/matlab/show/1718.php.
35