An Improved Approach in Fingerprint Recognition Algorithm

Patel, M. P.; Parikh, Satyen M.; Patel, Ashok R.

doi:10.1007/978-981-13-6295-8_12

Cited by 12 publications

(6 citation statements)

References 28 publications

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“…In [11], an algorithm was presented to identify the valid minutiae and increase the accuracy level and acceptance rate. The developed algorithm is split into two major steps: pre-processing and post-processing.…”

Section: Related Workmentioning

confidence: 99%

A Fingerprint-Based Verification Framework Using Harris and SURF Feature Detection Algorithms

2022

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Amongst all biometric-based personal authentication systems, a fingerprint that gives each person a unique identity is the most commonly used parameter for personal identification. In this paper, we present an automatic fingerprint-based authentication framework by means of fingerprint enhancement, feature extraction, and matching techniques. Initially, a variant of adaptive histogram equalization called CLAHE (contrast limited adaptive histogram equalization) along with a combination of FFT (fast Fourier transform), and Gabor filters are applied to enhance the contrast of fingerprint images. The fingerprint is then authenticated by picking a small amount of information from some local interest points called minutiae point features. These features are extracted from the thinned binary fingerprint image with a hybrid combination of Harris and SURF feature detectors to render significantly improved detection results. For fingerprint matching, the Euclidean distance between the corresponding Harris-SURF feature vectors of two feature points is used as a feature matching similarity measure of two fingerprint images. Moreover, an iterative algorithm called RANSAC (RANdom SAmple Consensus) is applied for fine matching and to automatically eliminate false matches and incorrect match points. Quantitative experimental results achieved on FVC2002 DB1 and FVC2000 DB1 public domain fingerprint databases demonstrate the good performance and feasibility of the proposed framework in terms of achieving average recognition rates of 95% and 92.5% for FVC2002 DB1 and FVC2000 DB1 databases, respectively.

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Section: Related Workmentioning

confidence: 99%

A Fingerprint-Based Verification Framework Using Harris and SURF Feature Detection Algorithms

2022

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“…It is crucial to occupy image enhancement techniques before the minutiae extraction process to get a more dependable estimation of the minutiae location [9,22,26]. Patel et al [24] presented an algorithm to identify the valid minutiae. The proposed algorithm increases the acceptance rate and accuracy level.…”

Section: Related Workmentioning

confidence: 99%

A functional enhancement on scarred fingerprint using sigmoid filtering

Kolivand

Hamid

Asadianfam

et al. 2022

Neural Comput & Applic

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Fingerprint has been widely used in biometric applications. Numerous established researches on image enhancement techniques have been done to improve the quality of fingerprint images. However, the production of low-quality images due to the presence of scars remains a challenge in biometrics. The scars damage the fingerprint minutiae information due to broken ridges and they reduce the accuracy of identification. This research developed an image enhancement approach to improve the quality of scarred fingerprint images to generate accurate minutiae extraction. To achieve the aim, the scarred image was improved by removing noise using a new filter, Median Sigmoid (MS), and the corrected ridges were reconstructed using ridges structure enhancement algorithm. This was done to enhance the broken ridges structure. MS filter is a combination of median filter and modified sigmoid function that improves the image contrast and simultaneously removes noise in the fingerprint image. Following that, the filtered image was used in the ridges structure enhancement process. To identify true minutiae, the broken ridges structure in the filtered image needed to be accurately verified. In the ridges structure reconstruction process, an algorithm was enhanced to identify the best value of Sigma parameter (σ) used in the Gaussian Low-pass filter to generate a better orientation image. The image is important to reconstruct the corrupted fingerprint ridges structure. The evaluation for the proposed approach used the National Institute of Standards and Technology Special Database 14, and the results showed a 37% improvement of the quality index in comparison to approaches found in related research. The findings of the evaluation showed that the proposed enhancement approach produced a better minutiae extraction result and this is very significant in the field of fingerprint image enhancement.

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“…Many algorithms can be used to analyze the fingerprint, like the Bozorth and Boyer-Moore algorithm, which can recognize fingerprints on a standard pattern fingerprint, a half-erased or rotated pattern [19]. There is new feature extraction technique based on fingerprint image blocks is presented [20], also many attempts to enhance most of the phases by working in two parts: pre-processing and postprocessing to remove the noise and make the clear fingerprint image for feature extraction [21] but the most famous is minutiae-based algorithm [22]. It is proposed to use simple pattern recognition to detect minutiae in fingerprints.…”

Section: Fingerprint Algorithmmentioning

confidence: 99%

Design and develop authentication in electronic payment systems based on IoT and biometric

Talib

Salman

2022

TELKOMNIKA

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Biometrics is a highly reliable technology where it has become possible to use the characteristics of a person or user (biometrics) along with traditional passwords, and we can even say that it has become an indispensable complement in modern authentication systems today, especially with regard to bank accounts, banks, financial technology (FinTech) internet of things (IoT) devices and all a process related to money and privacy, and biometric methods are multiple and increasing day by day, the most famous of which is (iris, face chart, palm, fingerprint, and others). Biometric systems are immune and immune from modern electronic attacks, such as plagiarism or electronic theft, because the authentication here takes place when all conditions are met. Then the authentication is done and the process is completed, and the aim is to reach the highest levels of accuracy and security and to make the user more comfortable to deal with these modern systems that provide him with many advantages and high privacy.

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An Improved Approach in Fingerprint Recognition Algorithm

Cited by 12 publications

References 28 publications

A Fingerprint-Based Verification Framework Using Harris and SURF Feature Detection Algorithms

A Fingerprint-Based Verification Framework Using Harris and SURF Feature Detection Algorithms

A functional enhancement on scarred fingerprint using sigmoid filtering

Design and develop authentication in electronic payment systems based on IoT and biometric

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