Human Identification via Face Recognition: Comparative Study

Prasad, Dr.R.Satya; Al-Ani, Muzhir Shaban; Nejres, Salwa Mohammed

doi:10.9790/0661-1903021722

Cited by 2 publications

(2 citation statements)

References 26 publications

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“…Research [18] has a main objective of designing an efficient face recognition approach by generating a matrix with a significant rank by applying the technique of singular value decomposition. A relative study is made by Prasad et al [19] scientific survey generated to study various methods and techniques with all the sufferings and benefits of these approaches. Al Ani and Al Waisy [20] presented an approach using a kernel machine for face detection from different views, the proposed algorithm shows powerful ability to effectively multi-view face detection.…”

Section: Related Workmentioning

confidence: 99%

New Feature-level Algorithm for a Face-fingerprint Integral Multi-biometrics Identification System

et al. 2022

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This article delves into the power of multi-biometric fusion for individual identification. a new feature-level algorithm is proposed that is the Dis-Eigen algorithm. Here, a feature-fusion framework is proposed for attaining better accuracy when identifying individuals for multiple biometrics. The framework, therefore, underpins the new multi-biometric system as it guides multi-biometric fusion applications at the feature phase for identifying individuals. In this regard, the Face-fingerprints of 20 individuals represented by 160 images were used in this framework . Experimental resultants of the proposed approach show 93.70 % identification rate with feature-level fusion multi-biometric individual identification.

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Section: Related Workmentioning

confidence: 99%

New Feature-level Algorithm for a Face-fingerprint Integral Multi-biometrics Identification System

et al. 2022

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“…This advantage allows iris identification as the most accurate and reliable biometric identification [35][36][37]. In the entire human population, there is no similarity two irises in their mathematical details, even between identical twins [38][39][40]. The probability of finding two people with an identical iris is almost approach zero, and the probability that two irises are similar; it is approximately 1 in 10 10 [41][42][43].…”

Section: Introductionmentioning

confidence: 99%

Efficient Biometric Iris Recognition Based on Iris Localization Approach

Al-Ani

2019

UHD J SCI TECH

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Biometric recognition is an emerging technology that has attracted more attention in recent years. This issue uses physiological and behavioral characteristics to identify an individual. The iris recognition approaches are among the most accurate biometric technologies with immense potential for use in global security applications. The purpose of this research is to implement an efficient approach to treat the diseased eye images in order to verify the second iris examination for the same person by inserting an improvement step to the iris recognition system. This step makes a correction of boundary around pupil and removes fraction regions. This approach demonstrates its ability to detect the inner limit of the iris. The obtained results shows that 90% success in the detection diseased eye images, which makes the iris recognition system more accurate and safe.

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Human Identification via Face Recognition: Comparative Study

Cited by 2 publications

References 26 publications

New Feature-level Algorithm for a Face-fingerprint Integral Multi-biometrics Identification System

New Feature-level Algorithm for a Face-fingerprint Integral Multi-biometrics Identification System

Efficient Biometric Iris Recognition Based on Iris Localization Approach

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