Generalized Fourier Descriptors with Applications to Objects Recognition in SVM Context View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2008-01

AUTHORS

Fethi Smach, Cedric Lemaître, Jean-Paul Gauthier, Johel Miteran, Mohamed Atri

ABSTRACT

This paper is about generalized Fourier descriptors, and their application to the research of invariants under group actions. A general methodology is developed, crucially related to Pontryagin’s, Tannaka’s, Chu’s and Tatsuuma’s dualities, from abstract harmonic analysis. Application to motion groups provides a general methodology for pattern recognition. This methodology generalizes the classical basic method of Fourier-invariants of contours of objects. In the paper, we use the results of this theory, inside a Support-Vector-Machine context, for 3D objects-recognition. As usual in practice, we classify 3D objects starting from 2D information. However our method is rather general and could be applied directly to 3D data, in other contexts. Our applications and comparisons with other methods are about human-face recognition, but also we provide tests and comparisons based upon standard data-bases such as the COIL data-base. Our methodology looks extremely efficient, and effective computations are rather simple and low cost. The paper is divided in two parts: first, the part relative to applications and computations, in a SVM environment. The second part is devoted to the development of the general theory of generalized Fourier-descriptors, with several new results, about their completeness in particular. These results lead to simple formulas for motion-invariants of images, that are “complete” in a certain sense, and that are used in the first part of the paper. The computation of these invariants requires only standard FFT estimations, and one dimensional integration. More... »

PAGES

43-71

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10851-007-0036-3

DOI

http://dx.doi.org/10.1007/s10851-007-0036-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1037308766


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

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": {
          "name": [
            "CES Laboratory, ENIS, University of Sfax, Sfax, Tunisia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Smach", 
        "givenName": "Fethi", 
        "id": "sg:person.07750776162.62", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07750776162.62"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Burgundy", 
          "id": "https://www.grid.ac/institutes/grid.5613.1", 
          "name": [
            "Le2i, UMR CNRS 5158, University of Burgundy, Dijon, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lema\u00eetre", 
        "givenName": "Cedric", 
        "id": "sg:person.014742406457.68", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014742406457.68"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Burgundy", 
          "id": "https://www.grid.ac/institutes/grid.5613.1", 
          "name": [
            "Le2i, UMR CNRS 5158, University of Burgundy, Dijon, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gauthier", 
        "givenName": "Jean-Paul", 
        "id": "sg:person.010301262074.33", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010301262074.33"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Burgundy", 
          "id": "https://www.grid.ac/institutes/grid.5613.1", 
          "name": [
            "Le2i, UMR CNRS 5158, University of Burgundy, Dijon, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Miteran", 
        "givenName": "Johel", 
        "id": "sg:person.012627671575.44", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012627671575.44"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Laboratory of Electronics (E\u03bcE), FSM, Monastir, Tunisia"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Atri", 
        "givenName": "Mohamed", 
        "id": "sg:person.012173542323.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012173542323.27"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/0004-3702(89)90066-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008277141"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0004-3702(89)90066-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008277141"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/b:visi.0000020671.28016.e8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009661627", 
          "https://doi.org/10.1023/b:visi.0000020671.28016.e8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-61275-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011755495", 
          "https://doi.org/10.1007/978-3-642-61275-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-61275-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011755495", 
          "https://doi.org/10.1007/978-3-642-61275-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0031-3203(95)00011-n", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014690078"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1006/acha.2000.0321", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017183212"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0031-3203(02)00353-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018691872"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01421486", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020275860", 
          "https://doi.org/10.1007/bf01421486"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01421486", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020275860", 
          "https://doi.org/10.1007/bf01421486"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1006/cviu.1999.0745", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020354592"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1020415117", 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-662-00102-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020415117", 
          "https://doi.org/10.1007/978-3-662-00102-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-662-00102-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020415117", 
          "https://doi.org/10.1007/978-3-662-00102-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/1-4020-2307-3_9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020949447", 
          "https://doi.org/10.1007/1-4020-2307-3_9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/b:visi.0000027790.02288.f2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024638466", 
          "https://doi.org/10.1023/b:visi.0000027790.02288.f2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bfb0069778", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025288822", 
          "https://doi.org/10.1007/bfb0069778"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bfb0069778", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025288822", 
          "https://doi.org/10.1007/bfb0069778"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bfb0084235", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029950704", 
          "https://doi.org/10.1007/bfb0084235"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0167-8655(94)90037-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032509378"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0167-8655(94)90037-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032509378"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01248403", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032770620", 
          "https://doi.org/10.1007/bf01248403"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1006/cviu.2001.0921", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035337904"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/130385.130401", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036379424"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-540-24670-1_18", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041420612", 
          "https://doi.org/10.1007/978-3-540-24670-1_18"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-540-24670-1_18", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041420612", 
          "https://doi.org/10.1007/978-3-540-24670-1_18"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1162/jocn.1991.3.1.71", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043225769"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1090/s0002-9947-1966-0195988-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046436193"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1090/s0273-0979-1979-14686-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049360384"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-75988-8_22", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049931023", 
          "https://doi.org/10.1007/978-3-642-75988-8_22"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1020715325630", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052063581", 
          "https://doi.org/10.1023/a:1020715325630"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/b:visi.0000029664.99615.94", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052687286", 
          "https://doi.org/10.1023/b:visi.0000029664.99615.94"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/21.101146", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061121280"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/34.55109", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061156497"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/34.598228", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061156617"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/72.554195", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061218851"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/1116025", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062866403"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/s0036144502400961", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062877780"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/s0036144502400961", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062877780"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1215/kjm/1250524377", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083510052"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/icpr.2004.1334492", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095229611"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1142/3838", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1098883908"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1142/0352", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1099037948"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5244/c.16.36", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1099368997"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2008-01", 
    "datePublishedReg": "2008-01-01", 
    "description": "This paper is about generalized Fourier descriptors, and their application to the research of invariants under group actions. A general methodology is developed, crucially related to Pontryagin\u2019s, Tannaka\u2019s, Chu\u2019s and Tatsuuma\u2019s dualities, from abstract harmonic analysis. Application to motion groups provides a general methodology for pattern recognition. This methodology generalizes the classical basic method of Fourier-invariants of contours of objects. In the paper, we use the results of this theory, inside a Support-Vector-Machine context, for 3D objects-recognition. As usual in practice, we classify 3D objects starting from 2D information. However our method is rather general and could be applied directly to 3D data, in other contexts. Our applications and comparisons with other methods are about human-face recognition, but also we provide tests and comparisons based upon standard data-bases such as the COIL data-base. Our methodology looks extremely efficient, and effective computations are rather simple and low cost. The paper is divided in two parts: first, the part relative to applications and computations, in a SVM environment. The second part is devoted to the development of the general theory of generalized Fourier-descriptors, with several new results, about their completeness in particular. These results lead to simple formulas for motion-invariants of images, that are \u201ccomplete\u201d in a certain sense, and that are used in the first part of the paper. The computation of these invariants requires only standard FFT estimations, and one dimensional integration.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10851-007-0036-3", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1041815", 
        "issn": [
          "0924-9907", 
          "1573-7683"
        ], 
        "name": "Journal of Mathematical Imaging and Vision", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "30"
      }
    ], 
    "name": "Generalized Fourier Descriptors with Applications to Objects Recognition in SVM Context", 
    "pagination": "43-71", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10851-007-0036-3"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "b1b9f1850c8550892c45dbd77738090e5601cee53b655383e94903db75364858"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1037308766"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10851-007-0036-3", 
      "https://app.dimensions.ai/details/publication/pub.1037308766"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-15T09:11", 
    "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/v90/0000000376_0000000376/records_56158_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs10851-007-0036-3"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

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/s10851-007-0036-3'

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/s10851-007-0036-3'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10851-007-0036-3'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10851-007-0036-3'


 

This table displays all metadata directly associated to this object as RDF triples.

213 TRIPLES      21 PREDICATES      63 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10851-007-0036-3 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author Nee0e9f69ea6849fc94c59603a610d4c9
4 schema:citation sg:pub.10.1007/1-4020-2307-3_9
5 sg:pub.10.1007/978-3-540-24670-1_18
6 sg:pub.10.1007/978-3-642-61275-6
7 sg:pub.10.1007/978-3-642-75988-8_22
8 sg:pub.10.1007/978-3-662-00102-8
9 sg:pub.10.1007/bf01248403
10 sg:pub.10.1007/bf01421486
11 sg:pub.10.1007/bfb0069778
12 sg:pub.10.1007/bfb0084235
13 sg:pub.10.1023/a:1020715325630
14 sg:pub.10.1023/b:visi.0000020671.28016.e8
15 sg:pub.10.1023/b:visi.0000027790.02288.f2
16 sg:pub.10.1023/b:visi.0000029664.99615.94
17 https://app.dimensions.ai/details/publication/pub.1020415117
18 https://doi.org/10.1006/acha.2000.0321
19 https://doi.org/10.1006/cviu.1999.0745
20 https://doi.org/10.1006/cviu.2001.0921
21 https://doi.org/10.1016/0004-3702(89)90066-0
22 https://doi.org/10.1016/0031-3203(95)00011-n
23 https://doi.org/10.1016/0167-8655(94)90037-x
24 https://doi.org/10.1016/s0031-3203(02)00353-9
25 https://doi.org/10.1090/s0002-9947-1966-0195988-5
26 https://doi.org/10.1090/s0273-0979-1979-14686-x
27 https://doi.org/10.1109/21.101146
28 https://doi.org/10.1109/34.55109
29 https://doi.org/10.1109/34.598228
30 https://doi.org/10.1109/72.554195
31 https://doi.org/10.1109/icpr.2004.1334492
32 https://doi.org/10.1137/1116025
33 https://doi.org/10.1137/s0036144502400961
34 https://doi.org/10.1142/0352
35 https://doi.org/10.1142/3838
36 https://doi.org/10.1145/130385.130401
37 https://doi.org/10.1162/jocn.1991.3.1.71
38 https://doi.org/10.1215/kjm/1250524377
39 https://doi.org/10.5244/c.16.36
40 schema:datePublished 2008-01
41 schema:datePublishedReg 2008-01-01
42 schema:description This paper is about generalized Fourier descriptors, and their application to the research of invariants under group actions. A general methodology is developed, crucially related to Pontryagin’s, Tannaka’s, Chu’s and Tatsuuma’s dualities, from abstract harmonic analysis. Application to motion groups provides a general methodology for pattern recognition. This methodology generalizes the classical basic method of Fourier-invariants of contours of objects. In the paper, we use the results of this theory, inside a Support-Vector-Machine context, for 3D objects-recognition. As usual in practice, we classify 3D objects starting from 2D information. However our method is rather general and could be applied directly to 3D data, in other contexts. Our applications and comparisons with other methods are about human-face recognition, but also we provide tests and comparisons based upon standard data-bases such as the COIL data-base. Our methodology looks extremely efficient, and effective computations are rather simple and low cost. The paper is divided in two parts: first, the part relative to applications and computations, in a SVM environment. The second part is devoted to the development of the general theory of generalized Fourier-descriptors, with several new results, about their completeness in particular. These results lead to simple formulas for motion-invariants of images, that are “complete” in a certain sense, and that are used in the first part of the paper. The computation of these invariants requires only standard FFT estimations, and one dimensional integration.
43 schema:genre research_article
44 schema:inLanguage en
45 schema:isAccessibleForFree false
46 schema:isPartOf N13f0a465b6d047999d70fbe631c1836f
47 Nc975eaf588d84428913d2e2b6b171205
48 sg:journal.1041815
49 schema:name Generalized Fourier Descriptors with Applications to Objects Recognition in SVM Context
50 schema:pagination 43-71
51 schema:productId N32bf202c953244038c5f72db83e64d41
52 N4dd428282e514f2889f8eaaff2111d60
53 Nbae1cc8931a94b348402a59c1ff28321
54 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037308766
55 https://doi.org/10.1007/s10851-007-0036-3
56 schema:sdDatePublished 2019-04-15T09:11
57 schema:sdLicense https://scigraph.springernature.com/explorer/license/
58 schema:sdPublisher N47cf643e4f244e129e06f25a6f9e2118
59 schema:url http://link.springer.com/10.1007%2Fs10851-007-0036-3
60 sgo:license sg:explorer/license/
61 sgo:sdDataset articles
62 rdf:type schema:ScholarlyArticle
63 N0e3717782bad4098a11529a8a74e645c schema:name CES Laboratory, ENIS, University of Sfax, Sfax, Tunisia
64 rdf:type schema:Organization
65 N13f0a465b6d047999d70fbe631c1836f schema:issueNumber 1
66 rdf:type schema:PublicationIssue
67 N32bf202c953244038c5f72db83e64d41 schema:name readcube_id
68 schema:value b1b9f1850c8550892c45dbd77738090e5601cee53b655383e94903db75364858
69 rdf:type schema:PropertyValue
70 N47cf643e4f244e129e06f25a6f9e2118 schema:name Springer Nature - SN SciGraph project
71 rdf:type schema:Organization
72 N4dd428282e514f2889f8eaaff2111d60 schema:name dimensions_id
73 schema:value pub.1037308766
74 rdf:type schema:PropertyValue
75 N897c9ae9a5a544ff93ee592323a57f09 rdf:first sg:person.012627671575.44
76 rdf:rest Nb4ff040e6017474b811ddf6eab656a29
77 N988294f53de843b19cafd59ffc9829df rdf:first sg:person.010301262074.33
78 rdf:rest N897c9ae9a5a544ff93ee592323a57f09
79 N98fcb2ff64e04857bafc550531e7885f schema:name Laboratory of Electronics (EμE), FSM, Monastir, Tunisia
80 rdf:type schema:Organization
81 Nb4ff040e6017474b811ddf6eab656a29 rdf:first sg:person.012173542323.27
82 rdf:rest rdf:nil
83 Nbae1cc8931a94b348402a59c1ff28321 schema:name doi
84 schema:value 10.1007/s10851-007-0036-3
85 rdf:type schema:PropertyValue
86 Nc5d8b6f91695425aae2a01a4fd573ba9 rdf:first sg:person.014742406457.68
87 rdf:rest N988294f53de843b19cafd59ffc9829df
88 Nc975eaf588d84428913d2e2b6b171205 schema:volumeNumber 30
89 rdf:type schema:PublicationVolume
90 Nee0e9f69ea6849fc94c59603a610d4c9 rdf:first sg:person.07750776162.62
91 rdf:rest Nc5d8b6f91695425aae2a01a4fd573ba9
92 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
93 schema:name Information and Computing Sciences
94 rdf:type schema:DefinedTerm
95 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
96 schema:name Artificial Intelligence and Image Processing
97 rdf:type schema:DefinedTerm
98 sg:journal.1041815 schema:issn 0924-9907
99 1573-7683
100 schema:name Journal of Mathematical Imaging and Vision
101 rdf:type schema:Periodical
102 sg:person.010301262074.33 schema:affiliation https://www.grid.ac/institutes/grid.5613.1
103 schema:familyName Gauthier
104 schema:givenName Jean-Paul
105 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010301262074.33
106 rdf:type schema:Person
107 sg:person.012173542323.27 schema:affiliation N98fcb2ff64e04857bafc550531e7885f
108 schema:familyName Atri
109 schema:givenName Mohamed
110 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012173542323.27
111 rdf:type schema:Person
112 sg:person.012627671575.44 schema:affiliation https://www.grid.ac/institutes/grid.5613.1
113 schema:familyName Miteran
114 schema:givenName Johel
115 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012627671575.44
116 rdf:type schema:Person
117 sg:person.014742406457.68 schema:affiliation https://www.grid.ac/institutes/grid.5613.1
118 schema:familyName Lemaître
119 schema:givenName Cedric
120 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014742406457.68
121 rdf:type schema:Person
122 sg:person.07750776162.62 schema:affiliation N0e3717782bad4098a11529a8a74e645c
123 schema:familyName Smach
124 schema:givenName Fethi
125 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07750776162.62
126 rdf:type schema:Person
127 sg:pub.10.1007/1-4020-2307-3_9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020949447
128 https://doi.org/10.1007/1-4020-2307-3_9
129 rdf:type schema:CreativeWork
130 sg:pub.10.1007/978-3-540-24670-1_18 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041420612
131 https://doi.org/10.1007/978-3-540-24670-1_18
132 rdf:type schema:CreativeWork
133 sg:pub.10.1007/978-3-642-61275-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011755495
134 https://doi.org/10.1007/978-3-642-61275-6
135 rdf:type schema:CreativeWork
136 sg:pub.10.1007/978-3-642-75988-8_22 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049931023
137 https://doi.org/10.1007/978-3-642-75988-8_22
138 rdf:type schema:CreativeWork
139 sg:pub.10.1007/978-3-662-00102-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020415117
140 https://doi.org/10.1007/978-3-662-00102-8
141 rdf:type schema:CreativeWork
142 sg:pub.10.1007/bf01248403 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032770620
143 https://doi.org/10.1007/bf01248403
144 rdf:type schema:CreativeWork
145 sg:pub.10.1007/bf01421486 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020275860
146 https://doi.org/10.1007/bf01421486
147 rdf:type schema:CreativeWork
148 sg:pub.10.1007/bfb0069778 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025288822
149 https://doi.org/10.1007/bfb0069778
150 rdf:type schema:CreativeWork
151 sg:pub.10.1007/bfb0084235 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029950704
152 https://doi.org/10.1007/bfb0084235
153 rdf:type schema:CreativeWork
154 sg:pub.10.1023/a:1020715325630 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052063581
155 https://doi.org/10.1023/a:1020715325630
156 rdf:type schema:CreativeWork
157 sg:pub.10.1023/b:visi.0000020671.28016.e8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009661627
158 https://doi.org/10.1023/b:visi.0000020671.28016.e8
159 rdf:type schema:CreativeWork
160 sg:pub.10.1023/b:visi.0000027790.02288.f2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024638466
161 https://doi.org/10.1023/b:visi.0000027790.02288.f2
162 rdf:type schema:CreativeWork
163 sg:pub.10.1023/b:visi.0000029664.99615.94 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052687286
164 https://doi.org/10.1023/b:visi.0000029664.99615.94
165 rdf:type schema:CreativeWork
166 https://app.dimensions.ai/details/publication/pub.1020415117 schema:CreativeWork
167 https://doi.org/10.1006/acha.2000.0321 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017183212
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1006/cviu.1999.0745 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020354592
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1006/cviu.2001.0921 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035337904
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1016/0004-3702(89)90066-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008277141
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1016/0031-3203(95)00011-n schema:sameAs https://app.dimensions.ai/details/publication/pub.1014690078
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1016/0167-8655(94)90037-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1032509378
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1016/s0031-3203(02)00353-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018691872
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1090/s0002-9947-1966-0195988-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046436193
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1090/s0273-0979-1979-14686-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1049360384
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1109/21.101146 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061121280
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1109/34.55109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061156497
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1109/34.598228 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061156617
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1109/72.554195 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061218851
192 rdf:type schema:CreativeWork
193 https://doi.org/10.1109/icpr.2004.1334492 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095229611
194 rdf:type schema:CreativeWork
195 https://doi.org/10.1137/1116025 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062866403
196 rdf:type schema:CreativeWork
197 https://doi.org/10.1137/s0036144502400961 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062877780
198 rdf:type schema:CreativeWork
199 https://doi.org/10.1142/0352 schema:sameAs https://app.dimensions.ai/details/publication/pub.1099037948
200 rdf:type schema:CreativeWork
201 https://doi.org/10.1142/3838 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098883908
202 rdf:type schema:CreativeWork
203 https://doi.org/10.1145/130385.130401 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036379424
204 rdf:type schema:CreativeWork
205 https://doi.org/10.1162/jocn.1991.3.1.71 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043225769
206 rdf:type schema:CreativeWork
207 https://doi.org/10.1215/kjm/1250524377 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083510052
208 rdf:type schema:CreativeWork
209 https://doi.org/10.5244/c.16.36 schema:sameAs https://app.dimensions.ai/details/publication/pub.1099368997
210 rdf:type schema:CreativeWork
211 https://www.grid.ac/institutes/grid.5613.1 schema:alternateName University of Burgundy
212 schema:name Le2i, UMR CNRS 5158, University of Burgundy, Dijon, France
213 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...