Classification is an important step towards fingerprint recognition. In the classification stage, fingerprints are usually associated to one of the five classes "A", "L", "R", "T", "W". The aim is to reduce the number of comparisons that are necessary for recognition. Many approaches to fingerprint classification have been proposed so far, but very few works investigated the potentialities of combining statistical and structural algorithms. In this paper, an approach to fusion of statistical and structural fingerprint classifiers is presented and experiments that show the potentialities of such fusion are reported
Fingerprint classification and matching are two key issues in automatic fingerprint recognition. Gen...
In this paper, we propose an approach for the classification of fingerprint databases. It is based o...
Abstract. A novel method to fingerprint classification, in which the naïve Bayes classifier (NB) and...
In this paper, an experimental comparison among three structural approaches to fingerprint classific...
This paper investigates the advantages of the combination of flat and structural approaches for fing...
Automatic Fingerprint Identification Systems (AFISs) are widely used for criminal investigations for...
A scheme is proposed for classifier combination at decision level which stresses the importance of c...
Automatic fingerprint classification has received considerable attention over the past decade. Desp...
Fingerprint classification provides an important indexing mechanism in a fingerprint database. An ac...
This paper presents a novel fingerprint classifier fusion algorithm using Dempster-Shafer theory con...
Abstract. We report about some experiments on the fingerprint database NIST-4 using different combin...
Using efficient classification methods is necessary for automatic fingerprint recognition system. Th...
Abstract manuscript proposes a move towards the sec-ondary level of fingerprint classification. This...
Fingerprints are the most widely used characteristics in systems that recognize a persons identity, ...
The paper describes a new approach for fingerprint classification, based on the distribution of loca...
Fingerprint classification and matching are two key issues in automatic fingerprint recognition. Gen...
In this paper, we propose an approach for the classification of fingerprint databases. It is based o...
Abstract. A novel method to fingerprint classification, in which the naïve Bayes classifier (NB) and...
In this paper, an experimental comparison among three structural approaches to fingerprint classific...
This paper investigates the advantages of the combination of flat and structural approaches for fing...
Automatic Fingerprint Identification Systems (AFISs) are widely used for criminal investigations for...
A scheme is proposed for classifier combination at decision level which stresses the importance of c...
Automatic fingerprint classification has received considerable attention over the past decade. Desp...
Fingerprint classification provides an important indexing mechanism in a fingerprint database. An ac...
This paper presents a novel fingerprint classifier fusion algorithm using Dempster-Shafer theory con...
Abstract. We report about some experiments on the fingerprint database NIST-4 using different combin...
Using efficient classification methods is necessary for automatic fingerprint recognition system. Th...
Abstract manuscript proposes a move towards the sec-ondary level of fingerprint classification. This...
Fingerprints are the most widely used characteristics in systems that recognize a persons identity, ...
The paper describes a new approach for fingerprint classification, based on the distribution of loca...
Fingerprint classification and matching are two key issues in automatic fingerprint recognition. Gen...
In this paper, we propose an approach for the classification of fingerprint databases. It is based o...
Abstract. A novel method to fingerprint classification, in which the naïve Bayes classifier (NB) and...