A New Phase-Correlation-Based Iris Matching for Degraded Images

Krichen, Emine; Garcia-Salicetti, Sonia; Dorizzi, Bernadette

doi:10.1109/tsmcb.2008.2009770

Cited by 16 publications

(2 citation statements)

References 17 publications

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“…An alternative to IR images based iris recognition is to use color information of iris for iris recognition. Krichen [10] used wavelet packets for iris identification using color iris images. Hugo [8] created a noisy iris database UBIRIS were gray scale images were used for experimentation.…”

Section: Iris Feature Extraction Using Histogram Of Color Modelsmentioning

confidence: 99%

Color Iris Authentication using Color Models

Narote¹,

Waghmare²

2017

IJCA

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Iris authentication is a popular method where persons are accurately authenticated. During authentication phase the features are extracted which are unique. Iris authentication uses IR images for authentication. This proposed work uses color iris images for authentication. Experiments are performed using ten different color models. This paper is focused on performance evaluation of color models used for color iris authentication. This proposed method is more reliable which cope up with different noises of color iris images. The experiments reveals the best selection of color model used for iris authentication. The proposed method is validated on UBIRIS noisy iris database. The results demonstrate that the accuracy is 92.1%, equal error rate of 0.072 and computational time is 0.039 seconds.

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Section: Iris Feature Extraction Using Histogram Of Color Modelsmentioning

confidence: 99%

Color Iris Authentication using Color Models

Narote¹,

Waghmare²

2017

IJCA

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“…Many researchers started working on this. Zhou et al [29], Zuo et al [30], Matey et al [31], Proenca et al [32], Medioni et al [33], He et al [34,35], Jinyu et al [30,36], Krichen et al [37], Hollingsworth et al [38,39], Perez et al [40], Thornton et al [41], Schuckers et al [42], and others also have worked to address this issue [42 -47]. They gave new methods for the compensation of non-ideal iris images in order to improve iris recognition performance.…”

Section: Acquisitionmentioning

confidence: 99%

Recent Trends in Iris Recognition

Birgale

Kokare

2011

Pattern Recognition, Machine Intelligence and Biometrics

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Security has been an issue these days. Every nation all over the world is very much concerned about its data security says cables obtained by WikiLeaks. Generally, one can identify oneself with a system by three basic methods based on Knowledge (what you know), Possession (what you have), and Reality (who you are). Both knowledge (passwords, PINs etc) and possession (e-tokens, ID cards etc) based methods are theft prone. Hence only the third type reality based (biometrics) are the options to rely on. Biometrics classified as physiological and behavioural traits are in use. Physiological traits like facial features, voice patterns, hand geometry, retinal patters, vein patterns, facial thermography, DNA matching, nailbed identification, ear shape recognition, finger prints and behavioural traits like signature dynamics, voice verification, gait analysis, keystroke dynamics etc all explored as biometric identifiers with varying levels of success. However, they have their own limitations. Nevertheless, iris has unique patterns, as it is a fact that no two-iris patterns are alike. That is one cannot be enrolled with the right eye and authenticated with the left. Uniqueness of iris motivates oneself to sustain it as a biometric authentication technique. After rigorous review of hundreds of papers on iris recognition systems, the authors are presenting this chapter. It contributes for the recent trends in iris recognition methodologies. IntroductionAn ocean of information with unlimited expanse and unfathomable depth got created and made accessible to all human beings through huge databases. Even if the ocean of information is available, only a small drop of this ocean, which is appropriate for the specific event, is the requirement of the day. Thus in the vast ocean of available databases picking the drop that quenches our thirst is the current field of research as the level of ocean of database is increasing day by day. The curse of e-wars in all the e-systems is calling for more and more secure systems and protection of data. At the same time, the matter of border security has become a matter of concern. Hence, the researchers have focused their attention on the secure biometric systems. Biometrics like the one fingerprints [1 -2], facial features [3], voice patterns, hand geometry, retinal patters, vein patterns, signature dynamics, iris etc

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