Embedded Palmprint Recognition System Using OMAP 3530

We have proposed in this paper an embedded palmprint recognition system using the dual-core OMAP 3530 platform. An improved algorithm based on palm code was proposed first. In this method, a Gabor wavelet is first convolved with the palmprint image to produce a response image, where local binary pat...

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Main Authors: Songhao Zheng, Zhen Ji, Shipei Wu, Linlin Shen
Format: Article
Language:English
Published: MDPI AG 2012-02-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/12/2/1482/
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author Songhao Zheng
Zhen Ji
Shipei Wu
Linlin Shen
author_facet Songhao Zheng
Zhen Ji
Shipei Wu
Linlin Shen
author_sort Songhao Zheng
collection DOAJ
description We have proposed in this paper an embedded palmprint recognition system using the dual-core OMAP 3530 platform. An improved algorithm based on palm code was proposed first. In this method, a Gabor wavelet is first convolved with the palmprint image to produce a response image, where local binary patterns are then applied to code the relation among the magnitude of wavelet response at the ccentral pixel with that of its neighbors. The method is fully tested using the public PolyU palmprint database. While palm code achieves only about 89% accuracy, over 96% accuracy is achieved by the proposed G-LBP approach. The proposed algorithm was then deployed to the DSP processor of OMAP 3530 and work together with the ARM processor for feature extraction. When complicated algorithms run on the DSP processor, the ARM processor can focus on image capture, user interface and peripheral control. Integrated with an image sensing module and central processing board, the designed device can achieve accurate and real time performance.
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spelling doaj.art-4f98d69c5e0449e3ad0ed570dbf6ae722022-12-22T02:10:16ZengMDPI AGSensors1424-82202012-02-011221482149310.3390/s120201482Embedded Palmprint Recognition System Using OMAP 3530Songhao ZhengZhen JiShipei WuLinlin ShenWe have proposed in this paper an embedded palmprint recognition system using the dual-core OMAP 3530 platform. An improved algorithm based on palm code was proposed first. In this method, a Gabor wavelet is first convolved with the palmprint image to produce a response image, where local binary patterns are then applied to code the relation among the magnitude of wavelet response at the ccentral pixel with that of its neighbors. The method is fully tested using the public PolyU palmprint database. While palm code achieves only about 89% accuracy, over 96% accuracy is achieved by the proposed G-LBP approach. The proposed algorithm was then deployed to the DSP processor of OMAP 3530 and work together with the ARM processor for feature extraction. When complicated algorithms run on the DSP processor, the ARM processor can focus on image capture, user interface and peripheral control. Integrated with an image sensing module and central processing board, the designed device can achieve accurate and real time performance.http://www.mdpi.com/1424-8220/12/2/1482/palmprint recognitionembedded systemGabor wavelet
spellingShingle Songhao Zheng
Zhen Ji
Shipei Wu
Linlin Shen
Embedded Palmprint Recognition System Using OMAP 3530
Sensors
palmprint recognition
embedded system
Gabor wavelet
title Embedded Palmprint Recognition System Using OMAP 3530
title_full Embedded Palmprint Recognition System Using OMAP 3530
title_fullStr Embedded Palmprint Recognition System Using OMAP 3530
title_full_unstemmed Embedded Palmprint Recognition System Using OMAP 3530
title_short Embedded Palmprint Recognition System Using OMAP 3530
title_sort embedded palmprint recognition system using omap 3530
topic palmprint recognition
embedded system
Gabor wavelet
url http://www.mdpi.com/1424-8220/12/2/1482/
work_keys_str_mv AT songhaozheng embeddedpalmprintrecognitionsystemusingomap3530
AT zhenji embeddedpalmprintrecognitionsystemusingomap3530
AT shipeiwu embeddedpalmprintrecognitionsystemusingomap3530
AT linlinshen embeddedpalmprintrecognitionsystemusingomap3530