Iris Biometrics for Embedded Systems

Liu-Jimenez, Judith; Sánchez-Reillo, Raúl; Fernandez-Saavedra, Belen

doi:10.1109/tvlsi.2009.2033701

Cited by 32 publications

(12 citation statements)

References 19 publications

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“…Although this platform does not show the complete scope of our proposal, the tools provided by the manufacturer allow showing our proposal feasibility. All the modules described in the Iris recognition algorithm have been implemented both in HW and SW. Further details of this implementation can be found in [20]. Table 1 shows a summary of the HW results obtained.…”

Section: Platform Used and Initial Datamentioning

confidence: 99%

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Optimisation of biometric ID tokens by using hardware/software co-design

et al. 2012

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In current society, the necessity of recognising people is increasing every day. Logical or physical access is restricted to authorised users, which in many cases have to provide tokens where their personal information is stored. At the same time, biometrics proposes a feasible solution for the recognition problem. The combination of both solutions is coming up front. However, up till now, owing to processing restrictions, these tokens are just able to store data and perform the last steps of the biometric recognition process. In this study, the authors propose a new system where tokens are based on hardware/ software (HW/SW) co-design, which allows computing most of the biometric process in them. This proposal covers several aspects which these systems are subject to, taking advantages of the two platforms they use for reducing computational time or HW area, and also to increase security or minimise misidentification errors. For testing this proposal, an Iris ID token has been implemented, showing different design alternatives adapted to different work scenarios.

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Section: Platform Used and Initial Datamentioning

confidence: 99%

“…For the different matching implementations possible [20], we have used the one based on a unique adder, as a compromise decision between time and area.…”

Section: Platform Used and Initial Datamentioning

confidence: 99%

Optimisation of biometric ID tokens by using hardware/software co-design

et al. 2012

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“…An iris biometrics system can be implemented to operate on a mobile phone and perform a quality assessment [8]. Iris biometric algorithms can be implemented on FPGAs [9] or on a DSP [10].…”

Section: Introductionmentioning

confidence: 99%

Efficient enhancement and matching for iris recognition using SURF

Ismail

Ali

Farag

2015

2015 5th National Symposium on Information Technology: Towards New Smart World (NSITNSW)

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Iris recognition is gaining more attention and the development of the field is increasing rapidly. This paper presents a complete iris recognition system. The iris features are obtained using Speeded Up Robust Features (SURF) after enhancing the image using Contrast Limited Adaptive Histogram Equalization (CLAHE). A novel matching algorithm based on applying fusion rules at different levels is proposed. The algorithm has the advantage of reduced data storage and fast matching. It can also handle efficiently the problem of rotation, scaling, illumination variation and occlusions. The proposed algorithm is implemented and tested using CASIA (V4) database. The recognition accuracies obtained are 99% using left images and 99.5% using right images. Results show that fusion of right and left images scores increases the recognition accuracy. The recognition accuracies obtained after fusion are 99.5% and 100% using minimum and sum rules respectively. Moreover, the proposed algorithm has an excellent robustness with respect to increasing the number of subjects.

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“…Relatedly, a ridge-based technique for fingerprint matching proposed by Marana and Jain (2005) used HT for extraction of fingerprint ridges by applying two masks that adaptively captured the maximum gray level values along the direction perpendicular to the ridge orientation. In addition, other experimental works are proposed by Kapadia and Patel (2013) on barcode scanning and Verma et al (2012), Liu-Jimenez et al (2011) and Mabrukar et al (2013) on iris. All these researches and many more in the literature that used HT were reported on detecting lines, signature, fingertip positions, nose tips and iris.…”

Section: Introductionmentioning

confidence: 99%

A New Hough Transform on Face Detection and Recognition Using Integrated Histograms

Sufyanu¹,

Susilawati²,

Yusuf³

et al. 2015

J. of Applied Sciences

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A B S T R A C T Hough Transform (HT) is one of the useful algorithms in pattern recognition. It is popularly used to detect straight lines, circles and curves in images. This study discovered a new feature detection and extraction using the HT. The intensity of the input image was enhanced and histogram plot of the stretched image was obtained. However, HT functions perform transformation of Hough matrix, locate peak values and superimpose a plot on the features representing the original image. Hence, face features were detected and the extracted features proceeded for verification. Cross Correlation Technique (CCT) and Euclidean Distance (ED) were computed to determine the similarity between test images and neutral image. The experiment on FEI face database demonstrated the effectiveness of the new technique and obtained recognition with minimal error. Furthermore, the application of HT was improved and the benefits of the proposed algorithm were verified. It is believed that, the discovery is new in the domain.

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Iris Biometrics for Embedded Systems

Cited by 32 publications

References 19 publications

Optimisation of biometric ID tokens by using hardware/software co-design

Optimisation of biometric ID tokens by using hardware/software co-design

Efficient enhancement and matching for iris recognition using SURF

A New Hough Transform on Face Detection and Recognition Using Integrated Histograms

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