Effective fingerprint recognition approach based on double fingerprint thumb

Al-Ani, Muzhir Shaban; Muhamad, Tishko N.; Muhamad, Hersh A.; Nuri, Ayub A.

doi:10.1109/crcsit.2017.7965537

Cited by 6 publications

(3 citation statements)

References 16 publications

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“…In fingerprint recognition orientation, several techniques are recommended for accuracy enhancement of the recognition, those techniques were different upon various criteria, certain of these proposals areas of interest was in the preprocessing stage of fingerprint images [5], implemented an approach for the features extraction of both right and left-hand thumbs using many levels of twodimensional discrete wavelet transform (2D-DWT), while another approach [6] used Discrete Cosine Transform (DCT) technique for extraction features [7], [8] presented techniques for fingerprint enhancement through localizing and recognizing the minutiae for minutiae extraction relying on the optimal thinning operation that took place in the preprocessing stage of fingerprint image. Prasad et al [9] proposed a system consisting of many stages starting from data gathering which includes fingerprint images belonging to many different people then pre-processing those depending on their characteristics, finally, the algorithm is used for the purpose of recognition of fingerprint.…”

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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“…Al‐Ani et al [14] presented a high‐performance method to perform finger recognition (FR). The method is based on real human fingerprint data samples and then implements the proposed FR approach.…”

Section: Related Workmentioning

confidence: 99%

FPR using machine learning with multi‐feature method

Kumar

Singh

2018

IET image process

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Biometrics authentication is considered as most secure and reliable method to recognise and identify person's identity. Researchers put efforts to find efficient ways to secure and classify the solutions to biometric problems. In this category, fingerprint recognition (FPR) is most widely used biometric trait for person identification/verification. The present work focuses an FPR technique, which uses the grey‐level difference method, discrete wavelet transforms and edge histogram descriptor for fingerprint representation and matching. Wavelet shrinkage used for noise removal in the image. Ridge flow estimation is calculated using the gradient approach. SVM and Hamming distance similarity measures are used for recognition. The experiment result has been tested on the standard 2000–2004 fingerprint verification competition dataset and the accuracy of proposed algorithm was reported to be well above 98%.

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“…The existing methods of shared secrets such as PINs or passwords, key devices, and smart cards, these are not sufficient in many applications [7][8][9]. Biometric characteristic can realize this issue that is unique and realize the characteristic of a human [10][11][12]. The use of biometrics for personal authentication becomes practical and considerably more accurate than the current methods [13][14][15].…”

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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Effective fingerprint recognition approach based on double fingerprint thumb

Cited by 6 publications

References 16 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

FPR using machine learning with multi‐feature method

Efficient Biometric Iris Recognition Based on Iris Localization Approach

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