Human ear recognition based on local multi-scale LBP features with city-block distance View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-11-07

AUTHORS

Zineb Youbi, Larbi Boubchir, Abdelhani Boukrouche

ABSTRACT

The use of the ear as a biometric modality has emerged in recent years. It makes it possible to differentiate people thanks to its stability over time and to the richness of its characteristics such as texture, color and size. This paper proposes a novel approach to ear recognition based on a variant of the Local Binary Pattern descriptor called Multi-scale Local Binary Pattern (MLBP). MLBP is calculated locally, by dividing the image into several equal blocks, to extract the ear features which will be used in the matching process to make a decision by detecting the similarities between the feature vectors using City-Block distance (CTB). The proposed method is evaluated on three reference ear databases: IIT Delhi I, IIT Delhi II and USTB-1. The analysis of the results obtained have clearly shown the robustness and the stability of the proposed ear recognition method which is highly competitive, achieving an attractive recognition performances in terms of identification rate at rank-1 up to: 98.40% for IIT Delhi I, 98.64% for IIT Delhi II, and 98.33% for USTB-1. More... »

PAGES

1-17

References to SciGraph publications

  • 2019. Human Gait State Prediction Using Cellular Automata and Classification Using ELM in MACHINE INTELLIGENCE AND SIGNAL ANALYSIS
  • 2016-05. Audiovisual synchrony assessment for replay attack detection in talking face biometrics in MULTIMEDIA TOOLS AND APPLICATIONS
  • 2008. The Ear as a Biometric in HANDBOOK OF BIOMETRICS
  • 2008-03. Perspective methods of human identification: Ear biometrics in OPTO-ELECTRONICS REVIEW
  • 2014. Ear Recognition Using Texture Features - A Novel Approach in ADVANCES IN SIGNAL PROCESSING AND INTELLIGENT RECOGNITION SYSTEMS
  • 2017-07. Biometric signature verification system based on freeman chain code and k-nearest neighbor in MULTIMEDIA TOOLS AND APPLICATIONS
  • 2019-02. Multispectral palmprint recognition using Pascal coefficients-based LBP and PHOG descriptors with random sampling in NEURAL COMPUTING AND APPLICATIONS
  • 2017-10. Finger contour profile based hand biometric recognition in MULTIMEDIA TOOLS AND APPLICATIONS
  • 2018-02-14. Human gait recognition using GEI-based local multi-scale feature descriptors in MULTIMEDIA TOOLS AND APPLICATIONS
  • 2017-03. Robust and accurate feature selection for humanoid push recovery and classification: deep learning approach in NEURAL COMPUTING AND APPLICATIONS
  • 2017-11. An optimized feature selection technique based on incremental feature analysis for bio-metric gait data classification in MULTIMEDIA TOOLS AND APPLICATIONS
  • 2008. Human Ear Recognition by Computer in NONE
  • 2017-05. Integrating appearance features and soft biometrics for person re-identification in MULTIMEDIA TOOLS AND APPLICATIONS
  • 2018-05-23. Beyond estimating discrete directions of walk: a fuzzy approach in MACHINE VISION AND APPLICATIONS
  • 2017-09. Human gait recognition based on Haralick features in SIGNAL, IMAGE AND VIDEO PROCESSING
  • 2008. Introduction to Biometrics in HANDBOOK OF BIOMETRICS
  • 2018-01. On Applicability of Tunable Filter Bank Based Feature for Ear Biometrics: A Study from Constrained to Unconstrained in JOURNAL OF MEDICAL SYSTEMS
  • 2018-11. Random permutation Maxout transform for cancellable facial template protection in MULTIMEDIA TOOLS AND APPLICATIONS
  • 2011. Computer Vision Using Local Binary Patterns in NONE
  • 2018-08-25. Fusion of PHOG and LDP local descriptors for kernel-based ear biometric recognition in MULTIMEDIA TOOLS AND APPLICATIONS
  • 1999. Biometrics, Personal Identification in Networked Society in NONE
  • 2015-07. Linear discriminant multi-set canonical correlations analysis (LDMCCA): an efficient approach for feature fusion of finger biometrics in MULTIMEDIA TOOLS AND APPLICATIONS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11042-018-6768-9

    DOI

    http://dx.doi.org/10.1007/s11042-018-6768-9

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1108054586


    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": {
              "alternateName": "Universit\u00e9 8 mai 1945 Guelma", 
              "id": "https://www.grid.ac/institutes/grid.442444.6", 
              "name": [
                "PI:MIS Laboratory, University of 8 Mai 1945 Guelma, Guelma, Algeria"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Youbi", 
            "givenName": "Zineb", 
            "id": "sg:person.010531032400.30", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010531032400.30"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Paris 8 University", 
              "id": "https://www.grid.ac/institutes/grid.15878.33", 
              "name": [
                "LIASD research Lab., University of Paris 8, 2 rue de la Libert\u00e9, 93526, Saint-Denis, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Boubchir", 
            "givenName": "Larbi", 
            "id": "sg:person.014157217771.40", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014157217771.40"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Universit\u00e9 8 mai 1945 Guelma", 
              "id": "https://www.grid.ac/institutes/grid.442444.6", 
              "name": [
                "PI:MIS Laboratory, University of 8 Mai 1945 Guelma, Guelma, Algeria"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Boukrouche", 
            "givenName": "Abdelhani", 
            "id": "sg:person.013612572172.43", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013612572172.43"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1016/j.eswa.2013.05.020", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000359987"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0262-8856(02)00003-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000470284"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.eswa.2016.03.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002719670"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.robot.2014.11.010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004216106"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1117/1.oe.55.9.093105", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004982029"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1117/12.2015946", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005729562"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1005980679", 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-84800-129-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005980679", 
              "https://doi.org/10.1007/978-1-84800-129-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-84800-129-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005980679", 
              "https://doi.org/10.1007/978-1-84800-129-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-319-04960-1_1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007615260", 
              "https://doi.org/10.1007/978-3-319-04960-1_1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00521-015-2089-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007874490", 
              "https://doi.org/10.1007/s00521-015-2089-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1117/1.jei.23.5.053008", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009918208"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-0-387-71041-9_1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011293849", 
              "https://doi.org/10.1007/978-0-387-71041-9_1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-0-387-71041-9_1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011293849", 
              "https://doi.org/10.1007/978-0-387-71041-9_1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.2478/s11772-007-0033-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018190313", 
              "https://doi.org/10.2478/s11772-007-0033-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11042-015-2848-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018486299", 
              "https://doi.org/10.1007/s11042-015-2848-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/00207160.2013.800194", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019801552"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11042-016-4070-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022597774", 
              "https://doi.org/10.1007/s11042-016-4070-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11042-016-4070-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022597774", 
              "https://doi.org/10.1007/s11042-016-4070-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.patcog.2012.06.020", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026374404"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-0-387-71041-9_7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028148790", 
              "https://doi.org/10.1007/978-0-387-71041-9_7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-0-387-71041-9_7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028148790", 
              "https://doi.org/10.1007/978-0-387-71041-9_7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0031-3203(95)00067-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035783933"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11042-016-3831-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038577954", 
              "https://doi.org/10.1007/s11042-016-3831-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11042-016-3831-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038577954", 
              "https://doi.org/10.1007/s11042-016-3831-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11042-016-4075-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039218152", 
              "https://doi.org/10.1007/s11042-016-4075-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11042-016-4075-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039218152", 
              "https://doi.org/10.1007/s11042-016-4075-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.patcog.2011.06.005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039455200"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/b117227", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042471084", 
              "https://doi.org/10.1007/b117227"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/b117227", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042471084", 
              "https://doi.org/10.1007/b117227"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.patrec.2011.11.013", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043341036"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0167-8655(87)90082-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046020656"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0167-8655(87)90082-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046020656"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1117/1.jei.25.1.013036", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046130157"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1048220511", 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-0-85729-748-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048220511", 
              "https://doi.org/10.1007/978-0-85729-748-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-0-85729-748-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048220511", 
              "https://doi.org/10.1007/978-0-85729-748-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11042-016-4110-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048363460", 
              "https://doi.org/10.1007/s11042-016-4110-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11042-016-4110-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048363460", 
              "https://doi.org/10.1007/s11042-016-4110-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11042-013-1817-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053262216", 
              "https://doi.org/10.1007/s11042-013-1817-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/jsen.2015.2389525", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061323788"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/jsen.2016.2570281", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061324978"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tase.2016.2594191", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061515724"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tassp.1980.1163426", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061518707"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tifs.2006.873653", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061629439"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tpami.2002.1017623", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061742396"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tpami.2003.1227990", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061742563"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11760-017-1066-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1083871066", 
              "https://doi.org/10.1007/s11760-017-1066-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11760-017-1066-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1083871066", 
              "https://doi.org/10.1007/s11760-017-1066-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1117/1.oe.56.4.043109", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085042038"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00521-017-3092-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091416258", 
              "https://doi.org/10.1007/s00521-017-3092-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00521-017-3092-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091416258", 
              "https://doi.org/10.1007/s00521-017-3092-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00521-017-3092-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091416258", 
              "https://doi.org/10.1007/s00521-017-3092-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00521-017-3092-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091416258", 
              "https://doi.org/10.1007/s00521-017-3092-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10916-017-0855-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093022717", 
              "https://doi.org/10.1007/s10916-017-0855-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/icpr.2002.1044746", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094023979"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tsp.2016.7760971", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094550864"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/icpr.2000.906202", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094719762"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/icpr.2008.4761843", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094884607"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/icpr.2008.4760935", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1095672573"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/icpr.2000.903698", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1095794917"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11042-018-5752-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101036501", 
              "https://doi.org/10.1007/s11042-018-5752-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1049/iet-bmt.2017.0251", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101149028"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11042-018-5956-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1103207941", 
              "https://doi.org/10.1007/s11042-018-5956-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/3180382.3180409", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1103308093"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/3180382.3180409", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1103308093"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00138-018-0939-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1104161429", 
              "https://doi.org/10.1007/s00138-018-0939-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00138-018-0939-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1104161429", 
              "https://doi.org/10.1007/s00138-018-0939-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.patcog.2018.06.008", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1104896129"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1142/s021812661950107x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1105687059"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-981-13-0923-6_12", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1106033653", 
              "https://doi.org/10.1007/978-981-13-0923-6_12"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11042-018-6489-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1106340068", 
              "https://doi.org/10.1007/s11042-018-6489-0"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2018-11-07", 
        "datePublishedReg": "2018-11-07", 
        "description": "The use of the ear as a biometric modality has emerged in recent years. It makes it possible to differentiate people thanks to its stability over time and to the richness of its characteristics such as texture, color and size. This paper proposes a novel approach to ear recognition based on a variant of the Local Binary Pattern descriptor called Multi-scale Local Binary Pattern (MLBP). MLBP is calculated locally, by dividing the image into several equal blocks, to extract the ear features which will be used in the matching process to make a decision by detecting the similarities between the feature vectors using City-Block distance (CTB). The proposed method is evaluated on three reference ear databases: IIT Delhi I, IIT Delhi II and USTB-1. The analysis of the results obtained have clearly shown the robustness and the stability of the proposed ear recognition method which is highly competitive, achieving an attractive recognition performances in terms of identification rate at rank-1 up to: 98.40% for IIT Delhi I, 98.64% for IIT Delhi II, and 98.33% for USTB-1.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s11042-018-6768-9", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1044869", 
            "issn": [
              "1380-7501", 
              "1573-7721"
            ], 
            "name": "Multimedia Tools and Applications", 
            "type": "Periodical"
          }
        ], 
        "name": "Human ear recognition based on local multi-scale LBP features with city-block distance", 
        "pagination": "1-17", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "35cfc829aecf66cfb6eedb25e3ffcf973687812e3115232a481cf0bc34c8bfcf"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s11042-018-6768-9"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1108054586"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s11042-018-6768-9", 
          "https://app.dimensions.ai/details/publication/pub.1108054586"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-10T20:56", 
        "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/v90/0000000001_0000000264/records_8684_00000578.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1007%2Fs11042-018-6768-9"
      }
    ]
     

    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/s11042-018-6768-9'

    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/s11042-018-6768-9'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11042-018-6768-9'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11042-018-6768-9'


     

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

    260 TRIPLES      21 PREDICATES      80 URIs      16 LITERALS      5 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s11042-018-6768-9 schema:about anzsrc-for:08
    2 anzsrc-for:0801
    3 schema:author N3c0f92df9af4438aa10be60999982128
    4 schema:citation sg:pub.10.1007/978-0-387-71041-9_1
    5 sg:pub.10.1007/978-0-387-71041-9_7
    6 sg:pub.10.1007/978-0-85729-748-8
    7 sg:pub.10.1007/978-1-84800-129-9
    8 sg:pub.10.1007/978-3-319-04960-1_1
    9 sg:pub.10.1007/978-981-13-0923-6_12
    10 sg:pub.10.1007/b117227
    11 sg:pub.10.1007/s00138-018-0939-6
    12 sg:pub.10.1007/s00521-015-2089-3
    13 sg:pub.10.1007/s00521-017-3092-7
    14 sg:pub.10.1007/s10916-017-0855-8
    15 sg:pub.10.1007/s11042-013-1817-x
    16 sg:pub.10.1007/s11042-015-2848-2
    17 sg:pub.10.1007/s11042-016-3831-2
    18 sg:pub.10.1007/s11042-016-4070-2
    19 sg:pub.10.1007/s11042-016-4075-x
    20 sg:pub.10.1007/s11042-016-4110-y
    21 sg:pub.10.1007/s11042-018-5752-8
    22 sg:pub.10.1007/s11042-018-5956-y
    23 sg:pub.10.1007/s11042-018-6489-0
    24 sg:pub.10.1007/s11760-017-1066-y
    25 sg:pub.10.2478/s11772-007-0033-5
    26 https://app.dimensions.ai/details/publication/pub.1005980679
    27 https://app.dimensions.ai/details/publication/pub.1048220511
    28 https://doi.org/10.1016/0031-3203(95)00067-4
    29 https://doi.org/10.1016/0167-8655(87)90082-1
    30 https://doi.org/10.1016/j.eswa.2013.05.020
    31 https://doi.org/10.1016/j.eswa.2016.03.004
    32 https://doi.org/10.1016/j.patcog.2011.06.005
    33 https://doi.org/10.1016/j.patcog.2012.06.020
    34 https://doi.org/10.1016/j.patcog.2018.06.008
    35 https://doi.org/10.1016/j.patrec.2011.11.013
    36 https://doi.org/10.1016/j.robot.2014.11.010
    37 https://doi.org/10.1016/s0262-8856(02)00003-3
    38 https://doi.org/10.1049/iet-bmt.2017.0251
    39 https://doi.org/10.1080/00207160.2013.800194
    40 https://doi.org/10.1109/icpr.2000.903698
    41 https://doi.org/10.1109/icpr.2000.906202
    42 https://doi.org/10.1109/icpr.2002.1044746
    43 https://doi.org/10.1109/icpr.2008.4760935
    44 https://doi.org/10.1109/icpr.2008.4761843
    45 https://doi.org/10.1109/jsen.2015.2389525
    46 https://doi.org/10.1109/jsen.2016.2570281
    47 https://doi.org/10.1109/tase.2016.2594191
    48 https://doi.org/10.1109/tassp.1980.1163426
    49 https://doi.org/10.1109/tifs.2006.873653
    50 https://doi.org/10.1109/tpami.2002.1017623
    51 https://doi.org/10.1109/tpami.2003.1227990
    52 https://doi.org/10.1109/tsp.2016.7760971
    53 https://doi.org/10.1117/1.jei.23.5.053008
    54 https://doi.org/10.1117/1.jei.25.1.013036
    55 https://doi.org/10.1117/1.oe.55.9.093105
    56 https://doi.org/10.1117/1.oe.56.4.043109
    57 https://doi.org/10.1117/12.2015946
    58 https://doi.org/10.1142/s021812661950107x
    59 https://doi.org/10.1145/3180382.3180409
    60 schema:datePublished 2018-11-07
    61 schema:datePublishedReg 2018-11-07
    62 schema:description The use of the ear as a biometric modality has emerged in recent years. It makes it possible to differentiate people thanks to its stability over time and to the richness of its characteristics such as texture, color and size. This paper proposes a novel approach to ear recognition based on a variant of the Local Binary Pattern descriptor called Multi-scale Local Binary Pattern (MLBP). MLBP is calculated locally, by dividing the image into several equal blocks, to extract the ear features which will be used in the matching process to make a decision by detecting the similarities between the feature vectors using City-Block distance (CTB). The proposed method is evaluated on three reference ear databases: IIT Delhi I, IIT Delhi II and USTB-1. The analysis of the results obtained have clearly shown the robustness and the stability of the proposed ear recognition method which is highly competitive, achieving an attractive recognition performances in terms of identification rate at rank-1 up to: 98.40% for IIT Delhi I, 98.64% for IIT Delhi II, and 98.33% for USTB-1.
    63 schema:genre research_article
    64 schema:inLanguage en
    65 schema:isAccessibleForFree false
    66 schema:isPartOf sg:journal.1044869
    67 schema:name Human ear recognition based on local multi-scale LBP features with city-block distance
    68 schema:pagination 1-17
    69 schema:productId Nb7d1cda3d10a47bcb6dce84a73d25921
    70 Ncd52ba0d66ad47b79f00e31a575ab017
    71 Ndda92c5a55f44ba1bc746650dca10f10
    72 schema:sameAs https://app.dimensions.ai/details/publication/pub.1108054586
    73 https://doi.org/10.1007/s11042-018-6768-9
    74 schema:sdDatePublished 2019-04-10T20:56
    75 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    76 schema:sdPublisher Nd671c28b932b4f4097e338ca128dfa67
    77 schema:url https://link.springer.com/10.1007%2Fs11042-018-6768-9
    78 sgo:license sg:explorer/license/
    79 sgo:sdDataset articles
    80 rdf:type schema:ScholarlyArticle
    81 N3c0f92df9af4438aa10be60999982128 rdf:first sg:person.010531032400.30
    82 rdf:rest N5d292f1987814208bca18ebab01a1dc2
    83 N5d292f1987814208bca18ebab01a1dc2 rdf:first sg:person.014157217771.40
    84 rdf:rest Nf78a308eac804be1a1ad46d7ed7b3c3a
    85 Nb7d1cda3d10a47bcb6dce84a73d25921 schema:name dimensions_id
    86 schema:value pub.1108054586
    87 rdf:type schema:PropertyValue
    88 Ncd52ba0d66ad47b79f00e31a575ab017 schema:name doi
    89 schema:value 10.1007/s11042-018-6768-9
    90 rdf:type schema:PropertyValue
    91 Nd671c28b932b4f4097e338ca128dfa67 schema:name Springer Nature - SN SciGraph project
    92 rdf:type schema:Organization
    93 Ndda92c5a55f44ba1bc746650dca10f10 schema:name readcube_id
    94 schema:value 35cfc829aecf66cfb6eedb25e3ffcf973687812e3115232a481cf0bc34c8bfcf
    95 rdf:type schema:PropertyValue
    96 Nf78a308eac804be1a1ad46d7ed7b3c3a rdf:first sg:person.013612572172.43
    97 rdf:rest rdf:nil
    98 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    99 schema:name Information and Computing Sciences
    100 rdf:type schema:DefinedTerm
    101 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
    102 schema:name Artificial Intelligence and Image Processing
    103 rdf:type schema:DefinedTerm
    104 sg:journal.1044869 schema:issn 1380-7501
    105 1573-7721
    106 schema:name Multimedia Tools and Applications
    107 rdf:type schema:Periodical
    108 sg:person.010531032400.30 schema:affiliation https://www.grid.ac/institutes/grid.442444.6
    109 schema:familyName Youbi
    110 schema:givenName Zineb
    111 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010531032400.30
    112 rdf:type schema:Person
    113 sg:person.013612572172.43 schema:affiliation https://www.grid.ac/institutes/grid.442444.6
    114 schema:familyName Boukrouche
    115 schema:givenName Abdelhani
    116 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013612572172.43
    117 rdf:type schema:Person
    118 sg:person.014157217771.40 schema:affiliation https://www.grid.ac/institutes/grid.15878.33
    119 schema:familyName Boubchir
    120 schema:givenName Larbi
    121 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014157217771.40
    122 rdf:type schema:Person
    123 sg:pub.10.1007/978-0-387-71041-9_1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011293849
    124 https://doi.org/10.1007/978-0-387-71041-9_1
    125 rdf:type schema:CreativeWork
    126 sg:pub.10.1007/978-0-387-71041-9_7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028148790
    127 https://doi.org/10.1007/978-0-387-71041-9_7
    128 rdf:type schema:CreativeWork
    129 sg:pub.10.1007/978-0-85729-748-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048220511
    130 https://doi.org/10.1007/978-0-85729-748-8
    131 rdf:type schema:CreativeWork
    132 sg:pub.10.1007/978-1-84800-129-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005980679
    133 https://doi.org/10.1007/978-1-84800-129-9
    134 rdf:type schema:CreativeWork
    135 sg:pub.10.1007/978-3-319-04960-1_1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007615260
    136 https://doi.org/10.1007/978-3-319-04960-1_1
    137 rdf:type schema:CreativeWork
    138 sg:pub.10.1007/978-981-13-0923-6_12 schema:sameAs https://app.dimensions.ai/details/publication/pub.1106033653
    139 https://doi.org/10.1007/978-981-13-0923-6_12
    140 rdf:type schema:CreativeWork
    141 sg:pub.10.1007/b117227 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042471084
    142 https://doi.org/10.1007/b117227
    143 rdf:type schema:CreativeWork
    144 sg:pub.10.1007/s00138-018-0939-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1104161429
    145 https://doi.org/10.1007/s00138-018-0939-6
    146 rdf:type schema:CreativeWork
    147 sg:pub.10.1007/s00521-015-2089-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007874490
    148 https://doi.org/10.1007/s00521-015-2089-3
    149 rdf:type schema:CreativeWork
    150 sg:pub.10.1007/s00521-017-3092-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091416258
    151 https://doi.org/10.1007/s00521-017-3092-7
    152 rdf:type schema:CreativeWork
    153 sg:pub.10.1007/s10916-017-0855-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093022717
    154 https://doi.org/10.1007/s10916-017-0855-8
    155 rdf:type schema:CreativeWork
    156 sg:pub.10.1007/s11042-013-1817-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1053262216
    157 https://doi.org/10.1007/s11042-013-1817-x
    158 rdf:type schema:CreativeWork
    159 sg:pub.10.1007/s11042-015-2848-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018486299
    160 https://doi.org/10.1007/s11042-015-2848-2
    161 rdf:type schema:CreativeWork
    162 sg:pub.10.1007/s11042-016-3831-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038577954
    163 https://doi.org/10.1007/s11042-016-3831-2
    164 rdf:type schema:CreativeWork
    165 sg:pub.10.1007/s11042-016-4070-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022597774
    166 https://doi.org/10.1007/s11042-016-4070-2
    167 rdf:type schema:CreativeWork
    168 sg:pub.10.1007/s11042-016-4075-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1039218152
    169 https://doi.org/10.1007/s11042-016-4075-x
    170 rdf:type schema:CreativeWork
    171 sg:pub.10.1007/s11042-016-4110-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1048363460
    172 https://doi.org/10.1007/s11042-016-4110-y
    173 rdf:type schema:CreativeWork
    174 sg:pub.10.1007/s11042-018-5752-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101036501
    175 https://doi.org/10.1007/s11042-018-5752-8
    176 rdf:type schema:CreativeWork
    177 sg:pub.10.1007/s11042-018-5956-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1103207941
    178 https://doi.org/10.1007/s11042-018-5956-y
    179 rdf:type schema:CreativeWork
    180 sg:pub.10.1007/s11042-018-6489-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1106340068
    181 https://doi.org/10.1007/s11042-018-6489-0
    182 rdf:type schema:CreativeWork
    183 sg:pub.10.1007/s11760-017-1066-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1083871066
    184 https://doi.org/10.1007/s11760-017-1066-y
    185 rdf:type schema:CreativeWork
    186 sg:pub.10.2478/s11772-007-0033-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018190313
    187 https://doi.org/10.2478/s11772-007-0033-5
    188 rdf:type schema:CreativeWork
    189 https://app.dimensions.ai/details/publication/pub.1005980679 schema:CreativeWork
    190 https://app.dimensions.ai/details/publication/pub.1048220511 schema:CreativeWork
    191 https://doi.org/10.1016/0031-3203(95)00067-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035783933
    192 rdf:type schema:CreativeWork
    193 https://doi.org/10.1016/0167-8655(87)90082-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046020656
    194 rdf:type schema:CreativeWork
    195 https://doi.org/10.1016/j.eswa.2013.05.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000359987
    196 rdf:type schema:CreativeWork
    197 https://doi.org/10.1016/j.eswa.2016.03.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002719670
    198 rdf:type schema:CreativeWork
    199 https://doi.org/10.1016/j.patcog.2011.06.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039455200
    200 rdf:type schema:CreativeWork
    201 https://doi.org/10.1016/j.patcog.2012.06.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026374404
    202 rdf:type schema:CreativeWork
    203 https://doi.org/10.1016/j.patcog.2018.06.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1104896129
    204 rdf:type schema:CreativeWork
    205 https://doi.org/10.1016/j.patrec.2011.11.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043341036
    206 rdf:type schema:CreativeWork
    207 https://doi.org/10.1016/j.robot.2014.11.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004216106
    208 rdf:type schema:CreativeWork
    209 https://doi.org/10.1016/s0262-8856(02)00003-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000470284
    210 rdf:type schema:CreativeWork
    211 https://doi.org/10.1049/iet-bmt.2017.0251 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101149028
    212 rdf:type schema:CreativeWork
    213 https://doi.org/10.1080/00207160.2013.800194 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019801552
    214 rdf:type schema:CreativeWork
    215 https://doi.org/10.1109/icpr.2000.903698 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095794917
    216 rdf:type schema:CreativeWork
    217 https://doi.org/10.1109/icpr.2000.906202 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094719762
    218 rdf:type schema:CreativeWork
    219 https://doi.org/10.1109/icpr.2002.1044746 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094023979
    220 rdf:type schema:CreativeWork
    221 https://doi.org/10.1109/icpr.2008.4760935 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095672573
    222 rdf:type schema:CreativeWork
    223 https://doi.org/10.1109/icpr.2008.4761843 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094884607
    224 rdf:type schema:CreativeWork
    225 https://doi.org/10.1109/jsen.2015.2389525 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061323788
    226 rdf:type schema:CreativeWork
    227 https://doi.org/10.1109/jsen.2016.2570281 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061324978
    228 rdf:type schema:CreativeWork
    229 https://doi.org/10.1109/tase.2016.2594191 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061515724
    230 rdf:type schema:CreativeWork
    231 https://doi.org/10.1109/tassp.1980.1163426 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061518707
    232 rdf:type schema:CreativeWork
    233 https://doi.org/10.1109/tifs.2006.873653 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061629439
    234 rdf:type schema:CreativeWork
    235 https://doi.org/10.1109/tpami.2002.1017623 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061742396
    236 rdf:type schema:CreativeWork
    237 https://doi.org/10.1109/tpami.2003.1227990 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061742563
    238 rdf:type schema:CreativeWork
    239 https://doi.org/10.1109/tsp.2016.7760971 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094550864
    240 rdf:type schema:CreativeWork
    241 https://doi.org/10.1117/1.jei.23.5.053008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009918208
    242 rdf:type schema:CreativeWork
    243 https://doi.org/10.1117/1.jei.25.1.013036 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046130157
    244 rdf:type schema:CreativeWork
    245 https://doi.org/10.1117/1.oe.55.9.093105 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004982029
    246 rdf:type schema:CreativeWork
    247 https://doi.org/10.1117/1.oe.56.4.043109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085042038
    248 rdf:type schema:CreativeWork
    249 https://doi.org/10.1117/12.2015946 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005729562
    250 rdf:type schema:CreativeWork
    251 https://doi.org/10.1142/s021812661950107x schema:sameAs https://app.dimensions.ai/details/publication/pub.1105687059
    252 rdf:type schema:CreativeWork
    253 https://doi.org/10.1145/3180382.3180409 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103308093
    254 rdf:type schema:CreativeWork
    255 https://www.grid.ac/institutes/grid.15878.33 schema:alternateName Paris 8 University
    256 schema:name LIASD research Lab., University of Paris 8, 2 rue de la Liberté, 93526, Saint-Denis, France
    257 rdf:type schema:Organization
    258 https://www.grid.ac/institutes/grid.442444.6 schema:alternateName Université 8 mai 1945 Guelma
    259 schema:name PI:MIS Laboratory, University of 8 Mai 1945 Guelma, Guelma, Algeria
    260 rdf:type schema:Organization
     




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


    ...