Fingerprint matching using an orientation-based minutia descriptor

Tico, Marius; Kuosmanen, Pauli

doi:10.1109/tpami.2003.1217604

Cited by 295 publications

(174 citation statements)

References 19 publications

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“…Tico and Kuosmanen [9] proposed the famous local orientation sampling structure around minutiae. We reinforce Tico's idea and propose a new minutiae orientation descriptor.…”

Section: Minutiae Ridge-valley Orientation Descriptormentioning

confidence: 99%

“…A number of attempts have been made to incorporate auxiliary information with minutiae as a local representation to decrease the ambiguousness. These methods consist of, local minutiae structure based [2]- [8], local orientation based [9], [10] and ridge feature based [11], [12] approaches. Among all of the minutiae representations, orientation based approaches can be considered as state-of-the-art ones and they significantly increase the discrimination power of single minutia.…”

Section: Introductionmentioning

confidence: 99%

“…Among all of the minutiae representations, orientation based approaches can be considered as state-of-the-art ones and they significantly increase the discrimination power of single minutia. Tico and Kuosmanen [9] proposed an orientation descriptor which sampling and encoding the orientation information around minutiae, Feng [10] extended this idea to a texturebased descriptor by incorporating the ridge frequency information with minutiae. However, these orientation-based methods suffered from border error in dealing with small fingerprint images.…”

Section: Introductionmentioning

confidence: 99%

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Hybrid Minutiae Descriptor for Narrow Fingerprint Verification

Isshiki

et al. 2017

IEICE Trans. Inf. & Syst.

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SUMMARYNarrow swipe sensor based systems have drawn more and more attention in recent years. However, the size of captured image is significantly smaller than that obtained from the traditional area fingerprint sensor. Under this condition the available minutiae number is also limited. Therefore, only employing minutiae with the standard associated feature can hardly achieve high verification accuracy. To solve this problem, we present a novel Hybrid Minutiae Descriptor (HMD) which consists of two modules. The first one: Minutiae Ridge-Valley Orientation Descriptor captures the orientation information around minutia and also the trace points located at associated ridge and valley. The second one: Gabor Binary Code extracts and codes the image patch around minutiae. The proposed HMD enhances the representation capability of minutiae feature, and can be matched very efficiently. Experiments conducted over public databases and the database captured by the narrow swipe sensor show that this innovative method gives rise to significant improvements in reducing FRR (False Reject Rate) and EER (Equal Error Rate). key words: narrow swipe sensor, fingerprint verification, hybrid minutiae descriptor, Gabor feature

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“…Tico and Kuosmanen [9] proposed the famous local orientation sampling structure around minutiae. We reinforce Tico's idea and propose a new minutiae orientation descriptor.…”

Section: Minutiae Ridge-valley Orientation Descriptormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Hybrid Minutiae Descriptor for Narrow Fingerprint Verification

Isshiki

et al. 2017

IEICE Trans. Inf. & Syst.

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“…Minutiae are clustered using the well-known Hough circles. A local orientation sampling structure is used to extract local features of the minutiae [7]. For a reference minutia m, L circles with radii r i , i=1,2,…L are considered as its local neighbourhood.…”

Section: Vmentioning

confidence: 99%

Advanced Partial Palmprint Matching Based on Repeated Adjoining Minutiae

Nayar¹

2015

IJRITCC

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Nowadays, high resolution palmprint images are used for recognition. The features that can be extracted from a high resolution palmprint image include the minutiae points. In this paper, instead of full palmprints, partial palmprints are used for matching. Partial refers to a part of the palmprint such as the thenar and hypothenar or hypothenar and interdigital areas. The minutiae can be easily located from the thinned palmprint image by using a window. Since there are a large number of minutiae present within a palmprint image, the minutiae are grouped into several clusters. The extracted minutiae are clustered using Hough circles. In order to avoid spurious minutiae resulting from the presence of immutable creases, radon transform is made use of. By selecting initial minutiae pairs, the entire matching is done by using repeated adjoining minutiae matching. The algorithm is developed and successfully tested with palmprint database.

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“…To enhance the matching rate some non-minutiae points are integrated with minutiae points. This provides additional nonminutiae information for calculating a more reliable degree of similarity between fingerprint impressions and also considerably improves the matching rate [10]. The fingerprint matching technique based on the energy vectors of fingerprints proposed by Nagaty [11] performs better than minutiae based approach.…”

Section: Related Workmentioning

confidence: 99%

Hartley Transform Based Fingerprint Matching

Bharkad¹,

Kokare²

2012

Journal of Information Processing Systems

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Abstract-TheHartley transform based feature extraction method is proposed for fingerprint matching. Hartley transform is applied on a smaller region that has been cropped around the core point. The performance of this proposed method is evaluated based on the standard database of Bologna University and the database of the FVC2002. We used the city block distance to compute the similarity between the test fingerprint and database fingerprint image. The results obtained are compared with the discrete wavelet transform (DWT) based method. The experimental results show that, the proposed method reduces the false acceptance rate (FAR) from 21.48% to 16.74 % based on the database of Bologna University and from 31.29% to 28.69% based on the FVC2002 database.

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Fingerprint matching using an orientation-based minutia descriptor

Cited by 295 publications

References 19 publications

Hybrid Minutiae Descriptor for Narrow Fingerprint Verification

Hybrid Minutiae Descriptor for Narrow Fingerprint Verification

Advanced Partial Palmprint Matching Based on Repeated Adjoining Minutiae

Hartley Transform Based Fingerprint Matching

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