Embedded Finger Vein Recognition System Using Raspberry Pi With Improved Region Of Interest

Finger Vein Recognition System (FVRS) is a biometric technology that identifies or verifies an individual based on unique vein patterns. Its performance is determined by the robustness of hardware and software development. According to the analysis of original FVRS, the software development stumbled...

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Main Author: Lim, Yuan Zhang
Format: Monograph
Language:English
Published: Universiti Sains Malaysia 2017
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Online Access:http://eprints.usm.my/53033/1/Embedded%20Finger%20Vein%20Recognition%20System%20Using%20Raspberry%20Pi%20With%20Improved%20Region%20Of%20Interest_Lim%20Yuan%20Zhang_E3_2017.pdf
http://eprints.usm.my/53033/
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spelling my.usm.eprints.53033 http://eprints.usm.my/53033/ Embedded Finger Vein Recognition System Using Raspberry Pi With Improved Region Of Interest Lim, Yuan Zhang T Technology TK Electrical Engineering. Electronics. Nuclear Engineering Finger Vein Recognition System (FVRS) is a biometric technology that identifies or verifies an individual based on unique vein patterns. Its performance is determined by the robustness of hardware and software development. According to the analysis of original FVRS, the software development stumbled upon image pre-processing stage particularly in the extraction of region of interest (ROI). The reason to the failure was because of the use of fixed window ROI extraction method, where the ROI was extracted using a predefined rectangle window. This method disregards the misplacement of finger and has no common reference point in extracting ROI. The objective of this project is to improve the accuracy of original FVRS by correcting the orientation of misaligned FV image and extracting ROI based on localised benchmark. In overall, this project contributed a new method of finger vein image segmentation using watershed segmentation with distance transform, then applied adapted methods to correct finger image orientation and extract consistent ROI using single sliding window based on phalangeal joints. OpenCV image processing library and C++ language were used in the development. The results proved that the improved system is able to correct the orientation of finger image regardless of finger placement during enrolment and verification, as well as obtaining ROI based on phalangeal joints. The performance evaluation shows that the verification accuracy of the improved system achieved 89.33%, an increase of 37.66% compared to original FVRS. Universiti Sains Malaysia 2017-06-01 Monograph NonPeerReviewed application/pdf en http://eprints.usm.my/53033/1/Embedded%20Finger%20Vein%20Recognition%20System%20Using%20Raspberry%20Pi%20With%20Improved%20Region%20Of%20Interest_Lim%20Yuan%20Zhang_E3_2017.pdf Lim, Yuan Zhang (2017) Embedded Finger Vein Recognition System Using Raspberry Pi With Improved Region Of Interest. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Elektrik & Elektronik. (Submitted)
institution Universiti Sains Malaysia
building Hamzah Sendut Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
url_provider http://eprints.usm.my/
language English
topic T Technology
TK Electrical Engineering. Electronics. Nuclear Engineering
spellingShingle T Technology
TK Electrical Engineering. Electronics. Nuclear Engineering
Lim, Yuan Zhang
Embedded Finger Vein Recognition System Using Raspberry Pi With Improved Region Of Interest
description Finger Vein Recognition System (FVRS) is a biometric technology that identifies or verifies an individual based on unique vein patterns. Its performance is determined by the robustness of hardware and software development. According to the analysis of original FVRS, the software development stumbled upon image pre-processing stage particularly in the extraction of region of interest (ROI). The reason to the failure was because of the use of fixed window ROI extraction method, where the ROI was extracted using a predefined rectangle window. This method disregards the misplacement of finger and has no common reference point in extracting ROI. The objective of this project is to improve the accuracy of original FVRS by correcting the orientation of misaligned FV image and extracting ROI based on localised benchmark. In overall, this project contributed a new method of finger vein image segmentation using watershed segmentation with distance transform, then applied adapted methods to correct finger image orientation and extract consistent ROI using single sliding window based on phalangeal joints. OpenCV image processing library and C++ language were used in the development. The results proved that the improved system is able to correct the orientation of finger image regardless of finger placement during enrolment and verification, as well as obtaining ROI based on phalangeal joints. The performance evaluation shows that the verification accuracy of the improved system achieved 89.33%, an increase of 37.66% compared to original FVRS.
format Monograph
author Lim, Yuan Zhang
author_facet Lim, Yuan Zhang
author_sort Lim, Yuan Zhang
title Embedded Finger Vein Recognition System Using Raspberry Pi With Improved Region Of Interest
title_short Embedded Finger Vein Recognition System Using Raspberry Pi With Improved Region Of Interest
title_full Embedded Finger Vein Recognition System Using Raspberry Pi With Improved Region Of Interest
title_fullStr Embedded Finger Vein Recognition System Using Raspberry Pi With Improved Region Of Interest
title_full_unstemmed Embedded Finger Vein Recognition System Using Raspberry Pi With Improved Region Of Interest
title_sort embedded finger vein recognition system using raspberry pi with improved region of interest
publisher Universiti Sains Malaysia
publishDate 2017
url http://eprints.usm.my/53033/1/Embedded%20Finger%20Vein%20Recognition%20System%20Using%20Raspberry%20Pi%20With%20Improved%20Region%20Of%20Interest_Lim%20Yuan%20Zhang_E3_2017.pdf
http://eprints.usm.my/53033/
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score 13.209306