Parallelizing Iris Recognition

Rakvic, Ryan; Ulis, Bradley J.; Broussard, Randy P.; Ives, Robert W.; Steiner, Neil

doi:10.1109/tifs.2009.2032012

Cited by 46 publications

(18 citation statements)

References 20 publications

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“…The Fig .3 shows the Sclera identical process. Blood barge patterns are unique to each individual, as are other biometric dope such as the patterns of the iris [23]. Unlike some biometric schemes, blood barge templates are almost impossible to counterfeit because they are located beneath the sheath's exterior.…”

Section: Proposed Work and Simulation Resultsmentioning

confidence: 99%

A Comprehensive Approach for Multi Biometric Recognition Using Sclera Vein and Finger Vein

K.R¹,

Vanitha²,

priya³

et al. 2015

International Journal of Advanced Research in Computer and Comm

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Multimodal biometrics use more than one means of biometric identification to achieve higher detection accuracy, since sometimes a single biometric is not good enough used to do identification and codification. Sclera and finger print strain is a new counterpart vein recognition method using a two-stage parallel approach for documentation and bouting. First, modeled a rotation-and rule-invariant Y shape descriptor based feature extraction method to efficiently eliminate most unlikely matches. Second, developed a weighted polar line sclera descriptor structure to incorporate mask information to reduce Graphics processing unit (GPU) awareness cost. Third, modeled a coarse-tofine two-rung matching approach. Finally, developed a weighing scheme to map the subtasks to GPU processing things. The experimental upshots show that the urged method can achieve dramatic processing speed improvement without compromising the detection accuracy. Here examined the previously proposed finger-strain identification approaches and develop a new approach that illustrates it superiority over prior published efforts. Then is to progress and examine two new score-level blends, i.e., holistic and non linear fusion, and comparatively evaluate them with more popular score-level fusion approaches to ascertain their effectiveness in the proposed scheme. The aim is to combine the upshots obtained by different biometric traits and significantly improve the overall accuracy of the biometric system.

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Section: Proposed Work and Simulation Resultsmentioning

confidence: 99%

A Comprehensive Approach for Multi Biometric Recognition Using Sclera Vein and Finger Vein

K.R¹,

Vanitha²,

priya³

et al. 2015

International Journal of Advanced Research in Computer and Comm

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“…Let ij I be the set of information source values and let 1 ij µ and 2 ij µ be the two membership functions that look at ij I differently. Then the divergent information is expressed as (29) We can use this measure in quantifying the quality of evaluation of any information source.…”

Section: Divergencementioning

confidence: 99%

“…Practical implementation of iris based biometrics requires faster and more efficient data storage and a possible solution to this problem is suggested using FPGA [29]. Spoofing of iris from iris codes is a sure bet and to circumvent this, counterfeiting measures are developed in [30].…”

Section: Literature Surveymentioning

confidence: 99%

An Introduction to Information Sets with an Application to Iris Based Authentication

Hanmandlu¹,

Bansal²,

Vasikarla³

2020

JMP

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This paper presents the information set which originates from a fuzzy set on applying the Hanman-Anirban entropy function to represent the uncertainty. Each element of the information set is called the information value which is a product of the information source value and its membership function value. The Hanman filter that modifies the information set is derived by using a filtering function. Adaptive Hanman-Anirban entropy is formulated and its properties are given. It paves the way for higher form of information sets called Hanman transforms that evaluate the information source based on the information obtained on it. Based on the information set six features, Effective Gaussian Information source value (EGI), Total Effective Gaussian Information (TEGI), Energy Feature (EF), Sigmoid Feature (SF), Hanman transform (HT) and Hanman Filter (HF) features are derived. The performance of the new features is evaluated on CASIA-IRIS-V3-Lamp database using both Inner Product Classifier (IPC) and Support Vector Machine (SVM). To tackle the problem of partially occluded eyes, majority voting method is applied on the iris strips and this enables better performance than that obtained when only a single iris strip is used.

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“…Calculate the bin where pixel j belongs to, m2 j ; 11: Store m1 j and m2 j into lookup table T ; 12: end for 13: end for 14: for Each direction i in 512 various directions do 15: for Each pixel j in ith direction do 16: Get the weight vote of j from table T , named w i;j ; 17: Get the vote of cell, ce i C D w i;j ; 18: end for 19 Human detection algorithms usually consist of four steps, which are gradient and direction computation, histograms generations, normalization, and classifying. However, this manner does not efficiently support the direct hardware implementations because many complex calculations are within the process.…”

Section: Algorithmsmentioning

confidence: 99%

Adaptive human detection approach using FPGA‐based parallel architecture in reconfigurable hardware

Gai

Qiu

et al. 2016

Concurrency and Computation

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Summary Currently, the rapid increment of human detections has been changing people's daily life, However, the implementation is still facing the challenges caused by the restrictions of power and hardware. The computation process results in a heavy workload even though prior researches had made efforts to reduce the complexity. We focus on this issue and propose a new approach that employs the binarization‐based optimization algorithm to simplify the computation processes. Our approach is designed to minimize the necessary calculations and memory space. Moreover, we have developed the field‐programmable gate array‐based parallel architecture to apply partial dynamic reconfiguration, which enables the remote configurations for the number of processing units. An experimental evaluation is completed in order to examine our proposed approach. According to our experimental results, the detection precision can reach a miss rate less than 1.97% and a false positive rate of 1%. The energy cost is also reduced up to 36% comparing with the prior methods. Copyright © 2016 John Wiley & Sons, Ltd.

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Parallelizing Iris Recognition

Cited by 46 publications

References 20 publications

A Comprehensive Approach for Multi Biometric Recognition Using Sclera Vein and Finger Vein

A Comprehensive Approach for Multi Biometric Recognition Using Sclera Vein and Finger Vein

An Introduction to Information Sets with an Application to Iris Based Authentication

Adaptive human detection approach using FPGA‐based parallel architecture in reconfigurable hardware

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