Figure 1 - uploaded by Horst Bischof
Content may be subject to copyright.
Fingerprint image acquired with a solid state sensor. Minutiae positions are highlighted. The right images show the minutiae types: ridge ending (top) and ridge bifurcation (bottom).
Source publication
Fingerprint matching is a common technique for biomet-ric authentication. Solid state sensors allow that fingerprint recognition is used in small sized embedded systems. The size of these sensors makes it necessary to store several im-pressions of the same finger. In order to reduce memory re-quirements and matching time all these images can be fus...
Similar publications
Singular points of a fingerprint image are special locations having high curvature properties. They can play a pivotal role in fingerprint normalization and reliable feature extraction. Accurate and efficient extraction of a singular point plays a major role in successful fingerprint recognition and indexing. In this paper, a novel deep learning ba...
we are here proposing a new algorithm to make a simpler approach to Fingerprint Recognition, to reduce False Rejection due to accident and to reduce the problem due to shrinking of finger due to winter season or water, namely Revolutionary Extended Spatial Point Extraction using Circular Technique for fingerprint recognition (R.E.S.P.E.C.T).
Nowadays, researchers are paying increasing attention to embedding systems. Cost reduction has lead to an increase in the number of platforms supporting the operating system Linux, jointly with the Raspberry Pi motherboard. Thus, embedding devices on Raspberry-Linux systems is a goal in order to make competitive commercial products. This paper pres...
Singular point detection is a primary step in fingerprint recognition, especially for fingerprint alignment and classification. But in present there are still some problems and challenges such as more false-positive singular points or inaccurate reference point localization. This paper proposes an accurate core point localization method based on sp...
![The Clarkson Fingerprint Generator (CFG) method [24] samples. Note the...](publication/361071320/figure/fig1/AS:11431281179230436@1691175385150/The-Clarkson-Fingerprint-Generator-CFG-method-24-samples-Note-the-lack-of-variation_Q320.jpg)
Public access to existing high‐resolution databases was discontinued. Besides, a hybrid database that contains fingerprints of different sensors with high and medium resolutions does not exist. A novel hybrid approach to synthesise realistic, multiresolution, and multisensor fingerprints to address these issues is presented. The first step was to i...
Citations
... Fingerprint alignment is an additional overhead required to be performed before matching fingerprints. There are various complicated procedures proposed in literature for aligning the query template with the registered template [20]. Some of them are based on the core point which require executing different algorithms for core point detection [16]. ...
... However, fingerprints show key points denoted as minutia and minutiae point clouds are well suited for relative alignment (e.g. [11]) in the match- In log end biometrics rotation is one of the main issues. Compared to an iris, the rotational range of a log end is not restricted and compared to a fingerprint just the pith as keypoint is available for alignment. ...
Tree log end biometrics is an approach to track logs from forest to further processing companies by means of log end images. The aim of this work is to investigate how to deal with the unrestricted rotational range of cross sections in log end images. Thus, the applicability of three different rotational pre-alignment strategies in the registration procedure is assessed. Template computation and matching is based on fingerprint and iris recognition techniques which were adopted and extended to work with log end images. To address these questions, a testset built up on 279 tree logs is utilized in the experiments. The evaluation assesses the basic performance of the rotational pre-alignment strategies and their impact on the verification and identification performances for different fingerprint- and iris-based configurations. Results indicate that rotational pre-alignment in the registration procedure is the main component to deal with rotation in log end biometrics. The best configurations achieve identification rates (Formula presented.). By showing that cross sections in log end images can be rotated to a distinctive position, this work is a first step towards real word log end biometrics.
... But choosing the reference minutiae directly induces that the adjacent minutiae pairs align well but the minutiae pairs far away do not align satisfactorily. Optimization of the alignment of reference minutiae to find a transformation which minimized the distance between all corresponding minutiae pairs was proposed by Ramoser [7]. Zhu [8] introduced global alignment of all corresponding minutiae pairs after selecting the reference minutiae. ...
Fingerprint is one of the biometrics used to identify a person. Alignment is an important step in fingerprint recognition, affecting greatly the speed and accuracy of matching. Eight types of Special ridges are introduced to align two fingerprints. The ridge with maximum of sampled curvature is used as reference ridges for initial alignment. And corresponding special ridges paired by topology get aligned by their features. The alignment parameters of translation and rotation finally come from all aligned special ridge pairs. Experiments show that alignment using special ridges is fast and robust.
... A brute force approach evaluating all possible solutions is very time consuming. In many literatures [1] [2], two minutia sets were aligned based on a list of attributes such as coordinates, direction, and types of minutiae. However, the distortions between two minutia sets extracted from different impressions of the same finger may include significant translation, rotation, scale, shear, local perturbation, occlusion and clutter, making it difficult to find the corresponding minutiae reliably with such insufficient information. ...
Although various algorithms have been proposed, accurate fingerprint matching remains an unresolved problem. This paper describes a minutiae based fingerprint matching algorithm that uses minutia descriptors to help finding the optimal global transformation between two different fingerprints quickly. Two different minutia descriptors, the local patch descriptor (LPD) and the geometrical configuration descriptor (GCD), are used in this paper. A small set of matched pairs between two different fingerprints are found first based on these minutia descriptors. A rough global transformation will be found in these small set of matched pairs by RANSAC algorithm, then a proposed method of verifying the matching result is applied to filter matched pairs that extracted from RANSAC algorithm. The final global transformation will be overdetermined by the filtered matched pairs. The matching result will be calculated by the final global transformation. Experimental results show that the occurrence of misalignment is dramatically reduced and that matching accuracy is improved at the same time.
... dry or wet fingers) or the surface condition of the fingerprint scanner. In order to overcome the limited performance of the fingerprint feature extraction from a single fingerprint, multi-impression approaches12345 have been proposed for the purpose of creating a template from multiple fingerprint images during enrollment. These multiimpression approaches can be distinguished based on the information source that is used, i.e., images or features. ...
... After coarse alignment, Jain et al. [1] modified an iterative closest point algorithm, while Lee et al. [2] suggested a distance map matching for fine alignment. Most of the feature-based approaches345 utilize minutiae as the feature and generate a template at the time of enrollment. Ramoser et al. [3] and Yau [4] merged corresponding minutiae into a single minutia but no minutiae evaluation is made. ...
... Most of the feature-based approaches345 utilize minutiae as the feature and generate a template at the time of enrollment. Ramoser et al. [3] and Yau [4] merged corresponding minutiae into a single minutia but no minutiae evaluation is made. Therefore, all the minutiae found in the feature extraction are assumed to be the true minutiae, which means that all false minutiae will be included in the template. ...
This paper proposes a minutiae-based template adaptation algorithm which can be applied after the fingerprint authentication process. The algorithm updates a template by using a query fingerprint, which is successfully verified by the fingerprint matcher as a high quality genuine input. This algorithm generates an updated minutiae set by using not only the minutiae but also local fingerprint quality information and utilizes a successive Bayesian estimation to evaluate the credibility of minutiae and their types. The proposed algorithm updates fingerprint minutiae information in the template as well as appends new minutiae from the query fingerprint. Preliminary experiments show an average 32.7% EER reduction and an even higher matching accuracy improvement at low false accept rates.
... A number of approaches for minutia-based registration have been proposed in the literature. These include methods based on a reference minutia pair [5,6,7] and on a local structure pair [8,9,10]. In [6] and [7], the minutia pair that results in the maximum number of the matching pairs is chosen as the reference pair. ...
... These include methods based on a reference minutia pair [5,6,7] and on a local structure pair [8,9,10]. In [6] and [7], the minutia pair that results in the maximum number of the matching pairs is chosen as the reference pair. The authors reported good performance. ...
... In all there are 258 latent cases. The results of our alignment algorithm are compared to those of alignment algorithm based on a reference minutiae pair (RMPA) similar to H.Ramoser's [7]. Table 1 gives the alignment statistics. ...
In this paper a novel distortion-tolerant fingerprint registration method based on clustering is proposed. In this method, minutiae features of the query fingerprint are divided into various clusters. Several local structure transformations are estimated by local structure sets. Then the global structures (centroid structures) are constructed according to the local structure transformation. The global transformation is determined by the score of local structure transformation together with the similarity level of the global structure. Experimental results show that this algorithm is robust for aligning fingerprints with a small number of minutia and heavy distortions. Such situations are often encountered in forensic applications
... A number of approaches for minutia-based registration have been proposed in the literature. These include methods based on a reference minutia pair [5,6,7] and on a local structure pair [8,9,10]. In [6] and [7], the minutia pair that results in the maximum number of the matching pairs is chosen as the reference pair. ...
... These include methods based on a reference minutia pair [5,6,7] and on a local structure pair [8,9,10]. In [6] and [7], the minutia pair that results in the maximum number of the matching pairs is chosen as the reference pair. The authors reported good performance. ...
... In all there are 258 latent cases. The results of our alignment algorithm are compared to those of alignment algorithm based on a reference minutiae pair (RMPA) similar to H.Ramoser's [7]. Table 1 gives the alignment statistics. ...
Summary In this paper a novel distortion-tolerant fingerprint registration method based on centroid structure vector (CSV) and Vector Line Segment (VLS), is proposed. In this method, minutia features of the query fingerprint are clustered into various clusters and a set of VLS is extracted. Several likely transformations between the query and the template images are estimated by using VLS sets. Then, CSV under each likely transformation is constructed by using the centroids of minutia clusters. The fine transformation is finally determined by the number of VLS pairs together with the similarity level of CSV. Experiment results show that this algorithm is an effective and efficient one for aligning fingerprints with a small number of minutia and heavy distortions. Such situations are often encountered in forensic applications.
Fingerprint matching with elastic distortion is very challenging to deal with, and severe fingerprint distortion usually leads to false non-matches. This paper proposes a phasebased registration algorithm which can effectively eliminate the distortion between fingerprints and therefore is beneficial to the subsequent fingerprint matching. The key of the proposed algorithm is to reconstruct the distortion field through unwrapping phase difference between two fingerprints. Experiments on FVC2004, Tsinghua Distorted Fingerprint (TDF) database, and NIST SD27 demonstrate that our algorithm outperforms other fingerprint registration methods, and significantly improves matching accuracy.
Contrary to popular belief, despite decades of research in fingerprints, reliable fingerprint recognition from large database is an open problem. Extracting features out of poor quality prints is the most challenging problem faced in this area. For that we need effective and efficient fingerprint matching algorithms that meet user requirements, to identify similarity. This paper gives a brief survey of current fingerprint matching methods and technical achievement in this area. The survey includes a large number of papers covering the research aspects of system design and applications of fingerprint matching, image feature representation and extraction. Furthermore future research directions are suggested.
