2010
AUTHORSDavrondzhon Gafurov , Patrick Bours , Bian Yang , Christoph Busch
ABSTRACTNowadays fingerprint verification system is the most widespread and accepted biometric technology that explores various features of the human fingers for this purpose. In general, every normal person has 10 fingers with different size. Although it is claimed that recognition performance with little fingers can be less accurate compared to other finger types, to our best knowledge, this has not been investigated yet. This paper presents our study on the topic of influence of the finger type into fingerprint recognition performance. For analysis we employ two fingerprint verification software packages (one public and one commercial). We conduct test on GUC100 multi sensor fingerprint database which contains fingerprint images of all 10 fingers from 100 subjects. Our analysis indeed confirms that performance with small fingers is less accurate than performance with the others fingers of the hand. It also appears that best performance is being obtained with thumb or index fingers. For example, performance deterioration from the best finger (i.e. index or thumb) to the worst fingers (i.e. small ones) can be in the range of 184%-1352%. More... »
PAGES1-7
Security Technology, Disaster Recovery and Business Continuity
ISBN
978-3-642-17609-8
978-3-642-17610-4
http://scigraph.springernature.com/pub.10.1007/978-3-642-17610-4_1
DOIhttp://dx.doi.org/10.1007/978-3-642-17610-4_1
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1052489285
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Artificial Intelligence and Image Processing",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Information and Computing Sciences",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Norwegian University of Science and Technology",
"id": "https://www.grid.ac/institutes/grid.5947.f",
"name": [
"Norwegian Information Security Lab, Gj\u00f8vik University College, P.O. Box 191, 2802, Gj\u00f8vik, Norway"
],
"type": "Organization"
},
"familyName": "Gafurov",
"givenName": "Davrondzhon",
"id": "sg:person.016427145551.22",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016427145551.22"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Norwegian University of Science and Technology",
"id": "https://www.grid.ac/institutes/grid.5947.f",
"name": [
"Norwegian Information Security Lab, Gj\u00f8vik University College, P.O. Box 191, 2802, Gj\u00f8vik, Norway"
],
"type": "Organization"
},
"familyName": "Bours",
"givenName": "Patrick",
"id": "sg:person.012362475737.51",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012362475737.51"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Norwegian University of Science and Technology",
"id": "https://www.grid.ac/institutes/grid.5947.f",
"name": [
"Norwegian Information Security Lab, Gj\u00f8vik University College, P.O. Box 191, 2802, Gj\u00f8vik, Norway"
],
"type": "Organization"
},
"familyName": "Yang",
"givenName": "Bian",
"id": "sg:person.014471467160.30",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014471467160.30"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Norwegian University of Science and Technology",
"id": "https://www.grid.ac/institutes/grid.5947.f",
"name": [
"Norwegian Information Security Lab, Gj\u00f8vik University College, P.O. Box 191, 2802, Gj\u00f8vik, Norway"
],
"type": "Organization"
},
"familyName": "Busch",
"givenName": "Christoph",
"id": "sg:person.011143356603.69",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011143356603.69"
],
"type": "Person"
}
],
"citation": [
{
"id": "https://app.dimensions.ai/details/publication/pub.1028717201",
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-1-84882-254-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028717201",
"https://doi.org/10.1007/978-1-84882-254-2"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-1-84882-254-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028717201",
"https://doi.org/10.1007/978-1-84882-254-2"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1504/ijcat.2009.024079",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1067441352"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/icar.2005.1507437",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1094803106"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/iccsa.2010.71",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1095306812"
],
"type": "CreativeWork"
}
],
"datePublished": "2010",
"datePublishedReg": "2010-01-01",
"description": "Nowadays fingerprint verification system is the most widespread and accepted biometric technology that explores various features of the human fingers for this purpose. In general, every normal person has 10 fingers with different size. Although it is claimed that recognition performance with little fingers can be less accurate compared to other finger types, to our best knowledge, this has not been investigated yet. This paper presents our study on the topic of influence of the finger type into fingerprint recognition performance. For analysis we employ two fingerprint verification software packages (one public and one commercial). We conduct test on GUC100 multi sensor fingerprint database which contains fingerprint images of all 10 fingers from 100 subjects. Our analysis indeed confirms that performance with small fingers is less accurate than performance with the others fingers of the hand. It also appears that best performance is being obtained with thumb or index fingers. For example, performance deterioration from the best finger (i.e. index or thumb) to the worst fingers (i.e. small ones) can be in the range of 184%-1352%.",
"editor": [
{
"familyName": "Kim",
"givenName": "Tai-hoon",
"type": "Person"
},
{
"familyName": "Fang",
"givenName": "Wai-chi",
"type": "Person"
},
{
"familyName": "Khan",
"givenName": "Muhammad Khurram",
"type": "Person"
},
{
"familyName": "Arnett",
"givenName": "Kirk P.",
"type": "Person"
},
{
"familyName": "Kang",
"givenName": "Heau-jo",
"type": "Person"
},
{
"familyName": "\u015al\u0119zak",
"givenName": "Dominik",
"type": "Person"
}
],
"genre": "chapter",
"id": "sg:pub.10.1007/978-3-642-17610-4_1",
"inLanguage": [
"en"
],
"isAccessibleForFree": false,
"isPartOf": {
"isbn": [
"978-3-642-17609-8",
"978-3-642-17610-4"
],
"name": "Security Technology, Disaster Recovery and Business Continuity",
"type": "Book"
},
"name": "Impact of Finger Type in Fingerprint Authentication",
"pagination": "1-7",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1052489285"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/978-3-642-17610-4_1"
]
},
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"fa062942ec141a044045b202e9d923297dfa97a1e87adb95ec3e6ea3d8d16751"
]
}
],
"publisher": {
"location": "Berlin, Heidelberg",
"name": "Springer Berlin Heidelberg",
"type": "Organisation"
},
"sameAs": [
"https://doi.org/10.1007/978-3-642-17610-4_1",
"https://app.dimensions.ai/details/publication/pub.1052489285"
],
"sdDataset": "chapters",
"sdDatePublished": "2019-04-16T08:30",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000364_0000000364/records_72834_00000000.jsonl",
"type": "Chapter",
"url": "https://link.springer.com/10.1007%2F978-3-642-17610-4_1"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-17610-4_1'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-17610-4_1'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-17610-4_1'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-17610-4_1'
This table displays all metadata directly associated to this object as RDF triples.
126 TRIPLES
23 PREDICATES
32 URIs
20 LITERALS
8 BLANK NODES