Impact of Quality-Based Fusion Techniques for Video-Based Iris Recognition at a Distance

Othman, Nadia; Dorizzi, Bernadette

doi:10.1109/tifs.2015.2421314

Cited by 21 publications

(8 citation statements)

References 37 publications

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“…When the number of frames increases beyond 5, they observed that the poor quality of the additional frames counteracted the introduction of extra information. Following a similar vein, Othman et al [32], [33] expanded this idea by computing the quality of local image patches. For this purpose, they estimated a Gaussian Mixture Model (GMM) of clean iris texture distribution.…”

Section: B Reconstruction-based Methods In the Pixel Domainmentioning

confidence: 99%

A Survey of Super-Resolution in Iris Biometrics With Evaluation of Dictionary-Learning

et al. 2019

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The lack of resolution has a negative impact on the performance of image-based biometrics. While many generic super-resolution methods have been proposed to restore low-resolution images, they usually aim to enhance their visual appearance. However, an overall visual enhancement of biometric images does not necessarily correlate with a better recognition performance. Reconstruction approaches thus need to incorporate the specific information from the target biometric modality to effectively improve recognition performance. This paper presents a comprehensive survey of iris super-resolution approaches proposed in the literature. We have also adapted an eigen-patches' reconstruction method based on the principal component analysis eigen-transformation of local image patches. The structure of the iris is exploited by building a patch-position-dependent dictionary. In addition, image patches are restored separately, having their own reconstruction weights. This allows the solution to be locally optimized, helping to preserve local information. To evaluate the algorithm, we degraded the high-resolution images from the CASIA Interval V3 database. Different restorations were considered, with 15 × 15 pixels being the smallest resolution evaluated. To the best of our knowledge, this is the smallest resolutions employed in the literature. The experimental framework is complemented with six publicly available iris comparators that were used to carry out biometric verification and identification experiments. The experimental results show that the proposed method significantly outperforms both the bilinear and bicubic interpolations at a very low resolution. The performance of a number of comparators attains an impressive equal error rate as low as 5% and a Top-1 accuracy of 77%-84% when considering the iris images of only 15 × 15 pixels. These results clearly demonstrate the benefit of using trained super-resolution techniques to improve the quality of iris images prior to matching.

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Section: B Reconstruction-based Methods In the Pixel Domainmentioning

confidence: 99%

A Survey of Super-Resolution in Iris Biometrics With Evaluation of Dictionary-Learning

et al. 2019

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“…Othman N. and Dorizzi B [2] established a built up a excellence combination method to process the eminence amount for the iris picture. This degree relies upon the gaussian model to gauge the unadulterated iris surface circulation.…”

Section: Litrature Serveymentioning

confidence: 99%

“…Among the tactices which are presents in biometric system , the iris recognition is considered as the most steadfast biometric technique with less error rate. Recognizing the iris is the automatic biometric authentication tactic based on pattern recognition also statistical feature detection [2]. The biometric system can recognize the person by both behaviorally and physically, namely fingerprints, palm prints, face, signature, veins and voice [3].…”

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confidence: 99%

Iris Recognition at-a-Distance by Means of Chronological MBO-Based DBN

Shirke¹,

Rajabhushnam²

2019

IJITEE

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Now a days, Iris recognition is wieldy used for the identification of person. The superior bit of 1 countries exploits biometric system for safety reason with the conclusion goal that in runway boarding, custom freedom, gathering passage, etc. The Iris detection at-a-Distance (IAAD) framework is generally used to identify the person in most of the applications. In this system, different features of iris image are extracted in addition enhances the superiority of iris image. Over the span of the most recent ages there consume raised various structures to design and finish iris affirmation systems which works at longer separation going from one meter to sixty meter. Because of such long scope of iris detection schemes in addition iris attainment scheme provides for the best applications to the client. Therefore, It is necessary to design an effective algorithm for IAAD is necessary. In this article, an actual method for iris recognition is presents. A Chronological Monarch Butterfly Optimization -based Deep Belief Network (Chronological MBO-based DBN) technique is anticipated for iris detection.This technique algorithm is the combination of Chronological theory with the Monarch Butterfly Optimization. It is utilized to mastermind the sequential presumption of an iris picture. Additionally, the Hough Transform calculation is utilized for discovery of iris circle and edge. To enhance the accuracy of anticipated iris recognition system ScatT-Loop descriptor and the Local Gradient Pattern (LGP) are fed to the Chronological MBO-based DBN algorithm and these are castoff to abstract the dissimilar features of an iris picture. The dataset used for these tactices are UBIRIS.v1 For the normalization and segmentation of an iris image is done by by means of Dougman's rubber sheet model. This system is established on MATLAB for executing the Hough transform procedures also for reading the iris images. The simulation results shows that this system successfully recognize the iris at a distance 4 to 8 meter. Different performance parameters like as FAR accuracy, too FRR shows better results in this anticipated work.

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“…Othman N. and Dorizzi B [29] developed a quality fusion technique to compute the quality measure for the iris image. This measure depends on the gaussian model to estimate the pure iris texture distribution.…”

Section: Related Workmentioning

confidence: 99%

Biometric Private Iris Recognition From An Image at Long Distance: A survey

Shirke¹,

Rajabhushnam²

2019

IJEAT

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The specially finished annular element of the person eye which is remotely visible is - iris. This iris recognition is useful to identify the individual. In number of applications the iris recognition system is used. Most of the countries uses biometric system for security purpose such that in airfield boarding, custom clearance, congregation entrance and so on. The Indian government also uses biometric system for identification of citizen in different applications like as in rashan shop, Aadhar project, in different government exam forms and registration dept. etc. The customary iris recognition systems develop near infrared (NIR) sensors to obtain pictures of the iris. But in this method the iris can acquire distance less than 1 meter. In the course of the last several years, there have been different designs to plan and complete iris acknowledgment frameworks which operates at longer distance ranging from 1 meter to 60 meter. Therefore, due to such long range of iris recognition systems and iris acquisition system gives to the best applications to the client. In this paper, an effective technique for iris recognition is present to identify the individual. It uses iris-recognition-at-a-distance (IAAD) system and state-of-the-art design methods to audits the iris recognition system. The primary point of this article is analyzing the criticalness and employments of IAAD systems with respect to human recognition, the review of existing IAAD structures, comparison of different method which are already implemented in literature and improvement of IAAD accuracy along with iris.

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Impact of Quality-Based Fusion Techniques for Video-Based Iris Recognition at a Distance

Cited by 21 publications

References 37 publications

A Survey of Super-Resolution in Iris Biometrics With Evaluation of Dictionary-Learning

A Survey of Super-Resolution in Iris Biometrics With Evaluation of Dictionary-Learning

Iris Recognition at-a-Distance by Means of Chronological MBO-Based DBN

Biometric Private Iris Recognition From An Image at Long Distance: A survey

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