Ridge-Based Fingerprint Recognition

Xie, Xiaolin; Su, Fei; Cai, Anni

doi:10.1007/11608288_37

Cited by 10 publications

(7 citation statements)

References 7 publications

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“…Missing minutiae because of a smaller capturing area may well affect discrimination. Fine ridge details, such as width, edge contour, and pores, are highly distinctive features [ 16 , 17 , 18 , 19 ]. However, as can be seen in Figure 2 , these features cannot be reliably detected.…”

Section: Fingerprint Sensor Interoperability Problem and Feature Ementioning

confidence: 99%

A Large-Scale Study of Fingerprint Matching Systems for Sensor Interoperability Problem

AlShehri

Aboalsamh

AlZuair

2018

Sensors

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The fingerprint is a commonly used biometric modality that is widely employed for authentication by law enforcement agencies and commercial applications. The designs of existing fingerprint matching methods are based on the hypothesis that the same sensor is used to capture fingerprints during enrollment and verification. Advances in fingerprint sensor technology have raised the question about the usability of current methods when different sensors are employed for enrollment and verification; this is a fingerprint sensor interoperability problem. To provide insight into this problem and assess the status of state-of-the-art matching methods to tackle this problem, we first analyze the characteristics of fingerprints captured with different sensors, which makes cross-sensor matching a challenging problem. We demonstrate the importance of fingerprint enhancement methods for cross-sensor matching. Finally, we conduct a comparative study of state-of-the-art fingerprint recognition methods and provide insight into their abilities to address this problem. We performed experiments using a public database (FingerPass) that contains nine datasets captured with different sensors. We analyzed the effects of different sensors and found that cross-sensor matching performance deteriorates when different sensors are used for enrollment and verification. In view of our analysis, we propose future research directions for this problem.

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Section: Fingerprint Sensor Interoperability Problem and Feature Ementioning

confidence: 99%

A Large-Scale Study of Fingerprint Matching Systems for Sensor Interoperability Problem

AlShehri

Aboalsamh

AlZuair

2018

Sensors

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“…FingerCode features have been used in later research [7,122,176]. Isolated orientation [91] or ridge information [169] can also be used for matching. Finally, when high resolution images are available, level-3 features such as sweat pores, dots and incipient ridges can be used instead of minutiae [68,103].…”

Section: Correlation-based Techniques and Matching Without Minutiaementioning

confidence: 99%

A survey on fingerprint minutiae-based local matching for verification and identification: Taxonomy and experimental evaluation

Peralta

Galar

Triguero

et al. 2015

Information Sciences

128

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Fingerprint recognition has found a reliable application for verification or identification of people in biometrics. Globally, fingerprints can be viewed as valuable traits due to several perceptions observed by the experts; such as the distinctiveness and the permanence on humans and the performance in real applications. Among the main stages of fingerprint recognition, the automated matching phase has received much attention from the early years up to nowadays. This paper is devoted to review and categorize the vast number of fingerprint matching methods proposed in the specialized literature. In particular, we focus on local minutiae-based matching algorithms, which provide good performance with an excellent trade-off between efficacy and efficiency. We identify the main properties and differences of existing methods. Then, we include an experimental evaluation involving the most representative local minutiae-based matching models in both verification and evaluation tasks. The results obtained will be discussed in detail, supporting the description of future directions.

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“…To avoid faulty matching and improve verification performance, many researchers have investigated the preprocessing of fingerprint images for improving fingerprint verification performance, enhancement of the registered templates' quality, adoption of fingerprint matching methods that can use the extracted templates effectively, and template protection for preventing leaks of registered templates. Many studies on methods for overcoming the problems associated with the fingerprint matching method using direction filters (instead of minutiae), phase information, and fingerprint images have been carried out [10][11][12][13][14][15].…”

Section: Proposed Fingerprint Verification Systemmentioning

confidence: 99%

Security Enhancement for Smartphone Using Biometrics in Cyber-Physical Systems

Chae

Moon

et al. 2014

International Journal of Distributed Sensor Networks

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With the expansion of the Cyber-Physical System (CPS) concept, smartphones have come to constitute a competitive platform that connects humans and the surrounding physical world. Along with the communication functions and mobility of cellular phones, smartphones have various sensors in addition to greatly enhanced performances and storage space compared with existing cellular phones. However the "unlock" process of smartphones and the need for user passwords when accessing SNSs prove to be great weaknesses in smartphone security. Therefore, smartphone security should be enhanced through biometrics, which can make up for the shortcomings of passwords. The present study proposes minutiae-ridge based fingerprint verification for enhancing the security of fingerprint verification, a biometrics, to improve smartphone security. To evaluate the proposed minutiae-ridge based fingerprint verification performance in smartphones, its performance was compared with existing fingerprint verification methods in terms of Equal Error Rate (EER), False Non-Match Rate (FNMR), and required number of cycles. The results show that although the required number of cycles increased by 1.5% with the proposed method, EER and FNMR improved by 53% and 92%, respectively.

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Ridge-Based Fingerprint Recognition

Cited by 10 publications

References 7 publications

A Large-Scale Study of Fingerprint Matching Systems for Sensor Interoperability Problem

A Large-Scale Study of Fingerprint Matching Systems for Sensor Interoperability Problem

A survey on fingerprint minutiae-based local matching for verification and identification: Taxonomy and experimental evaluation

Security Enhancement for Smartphone Using Biometrics in Cyber-Physical Systems

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