A minutiae matching algorithm in fingerprint verification

This paper describes an embedded minutia-based matching algorithm using the reference point neighborhoods minutiae. The proposed matching algorithm is implemented in restricted environments such as smart card devices requiring careful monitoring of both memory and processing time usage. The proposed algorithm uses a circular tessellation to encode fingerprint features in neighborhood minutia localization binary codes. The objective of the present study is the development of a new matching approach which reduces both computing time and required space memory for fingerprint matching on Java Card. The main advantage of our approach is avoiding the implicit alignment of fingerprint images during the matching process while improving the fingerprint verification accuracy. Tests carried out on the public fingerprint databases DB1-a and DB2-a of FVC2002 have shown the effectiveness of our approach.

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A Multiple Substructure Matching Algorithm for Fingerprint Verification

Lecture Notes in Computer Science - Progress in Pattern Recognition, Image Analysis and Applications ◽

10.1007/978-3-540-76725-1_19 ◽

2007 ◽

pp. 172-181 ◽

Cited By ~ 3

Author(s):

Mabel Iglesias Ham ◽

Yilian Bazán Pereira ◽

Edel B. García Reyes

Keyword(s):

Fingerprint Verification ◽

Matching Algorithm

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Image enhancement and minutiae matching in fingerprint verification

Pattern Recognition Letters ◽

10.1016/s0167-8655(02)00376-8 ◽

2003 ◽

Vol 24 (9-10) ◽

pp. 1349-1360 ◽

Cited By ~ 86

Author(s):

Yuliang He ◽

Jie Tian ◽

Xiping Luo ◽

Tanghui Zhang

Keyword(s):

Image Enhancement ◽

Fingerprint Verification ◽

Minutiae Matching

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A Secured Contactless Fingerprint Verification Method Using a Minutiae Matching Technique

Advancements in Computer Vision and Image Processing - Advances in Computer and Electrical Engineering ◽

10.4018/978-1-5225-5628-2.ch009 ◽

2018 ◽

pp. 221-245

Author(s):

Tahirou Djara ◽

Marc Kokou Assogba ◽

Antoine Vianou

Keyword(s):

Orientation Angle ◽

Input Image ◽

Fingerprint Matching ◽

Fingerprint Verification ◽

Excessive Pressure ◽

Verification Method ◽

Template Protection ◽

Euclidean Distances ◽

Minutiae Matching ◽

Future Work

Most matching or verification phases of fingerprint systems use minutiae types and orientation angle to find matched minutiae pairs from the input and template fingerprints. Unfortunately, due to some non-linear distortions, like excessive pressure and fingers twisting during enrollment, this process can cause the minutiae features to be distorted from the original. The authors are interested in a fingerprint matching method using contactless images for fingerprint verification. After features extraction, they compute Euclidean distances between template minutiae (bifurcation and ending points) and input image minutiae. They compute then after bifurcation ridges orientation angles and ending point orientations. In the decision stage, they analyze the similarity between templates. The proposed algorithm has been tested on a set of 420 fingerprint images. The verification accuracy is found to be acceptable and the experimental results are promising. Future work will enhance the proposed verification method by a new template protection technique.

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