Contour and Texture Analysis for Image Segmentation View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2000

AUTHORS

Jitendra Malik , Serge Belongie , Thomas Leung , Jianbo Shi

ABSTRACT

This paper provides an algorithm for partitioning gray-scale images into disjoint regions of coherent brightness and texture. Natural images contain both textured and untextured regions, so the cues of contour and texture differences are exploited simultaneously. Contours are treated in the intervening contour framework, while texture is analyzed using textons. Each of these cues has a domain of applicability, so to facilitate cue combination we introduce a gating operator based on the texturedness of the neighborhood at a pixel. Having obtained a local measure of how likely two nearby pixels are to belong to the same region, we use the spectral graph theoretic framework of normalized cuts to find partitions of the image into regions of coherent texture and brightness. Experimental results on a wide range of images are shown. More... »

PAGES

139-172

Book

TITLE

Perceptual Organization for Artificial Vision Systems

ISBN

978-1-4613-6986-8
978-1-4615-4413-5

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-4615-4413-5_9

DOI

http://dx.doi.org/10.1007/978-1-4615-4413-5_9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1046278747


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/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "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"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of Califonia, Berkeley, USA", 
          "id": "http://www.grid.ac/institutes/grid.30389.31", 
          "name": [
            "University of Califonia, Berkeley, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Malik", 
        "givenName": "Jitendra", 
        "id": "sg:person.01364521761.84", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01364521761.84"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Califonia, Berkeley, USA", 
          "id": "http://www.grid.ac/institutes/grid.30389.31", 
          "name": [
            "University of Califonia, Berkeley, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Belongie", 
        "givenName": "Serge", 
        "id": "sg:person.0632735744.68", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0632735744.68"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Califonia, Berkeley, USA", 
          "id": "http://www.grid.ac/institutes/grid.30389.31", 
          "name": [
            "University of Califonia, Berkeley, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Leung", 
        "givenName": "Thomas", 
        "id": "sg:person.016034550437.98", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016034550437.98"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Califonia, Berkeley, USA", 
          "id": "http://www.grid.ac/institutes/grid.30389.31", 
          "name": [
            "University of Califonia, Berkeley, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shi", 
        "givenName": "Jianbo", 
        "id": "sg:person.016214030753.30", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016214030753.30"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2000", 
    "datePublishedReg": "2000-01-01", 
    "description": "This paper provides an algorithm for partitioning gray-scale images into disjoint regions of coherent brightness and texture. Natural images contain both textured and untextured regions, so the cues of contour and texture differences are exploited simultaneously. Contours are treated in the intervening contour framework, while texture is analyzed using textons. Each of these cues has a domain of applicability, so to facilitate cue combination we introduce a gating operator based on the texturedness of the neighborhood at a pixel. Having obtained a local measure of how likely two nearby pixels are to belong to the same region, we use the spectral graph theoretic framework of normalized cuts to find partitions of the image into regions of coherent texture and brightness. Experimental results on a wide range of images are shown.", 
    "editor": [
      {
        "familyName": "Boyer", 
        "givenName": "Kim L.", 
        "type": "Person"
      }, 
      {
        "familyName": "Sarkar", 
        "givenName": "Sudeep", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-1-4615-4413-5_9", 
    "isAccessibleForFree": true, 
    "isPartOf": {
      "isbn": [
        "978-1-4613-6986-8", 
        "978-1-4615-4413-5"
      ], 
      "name": "Perceptual Organization for Artificial Vision Systems", 
      "type": "Book"
    }, 
    "keywords": [
      "gray-scale images", 
      "spectral graph theoretic framework", 
      "graph-theoretic framework", 
      "natural images", 
      "untextured regions", 
      "image segmentation", 
      "disjoint regions", 
      "nearby pixels", 
      "theoretic framework", 
      "images", 
      "texture differences", 
      "pixels", 
      "experimental results", 
      "texture analysis", 
      "framework", 
      "domain of applicability", 
      "algorithm", 
      "textons", 
      "coherent texture", 
      "segmentation", 
      "texture", 
      "contours", 
      "partition", 
      "domain", 
      "applicability", 
      "cue combination", 
      "operators", 
      "wide range", 
      "brightness", 
      "cues", 
      "texturedness", 
      "neighborhood", 
      "local measures", 
      "results", 
      "combination", 
      "measures", 
      "analysis", 
      "region", 
      "same region", 
      "cut", 
      "range", 
      "differences", 
      "paper"
    ], 
    "name": "Contour and Texture Analysis for Image Segmentation", 
    "pagination": "139-172", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1046278747"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-1-4615-4413-5_9"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-1-4615-4413-5_9", 
      "https://app.dimensions.ai/details/publication/pub.1046278747"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2022-12-01T06:46", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221201/entities/gbq_results/chapter/chapter_101.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-1-4615-4413-5_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.10.1007/978-1-4615-4413-5_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.10.1007/978-1-4615-4413-5_9'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-1-4615-4413-5_9'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-1-4615-4413-5_9'


 

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

128 TRIPLES      22 PREDICATES      68 URIs      61 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-1-4615-4413-5_9 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author Nd37c7b89a0984347b7fa105006bd3a19
4 schema:datePublished 2000
5 schema:datePublishedReg 2000-01-01
6 schema:description This paper provides an algorithm for partitioning gray-scale images into disjoint regions of coherent brightness and texture. Natural images contain both textured and untextured regions, so the cues of contour and texture differences are exploited simultaneously. Contours are treated in the intervening contour framework, while texture is analyzed using textons. Each of these cues has a domain of applicability, so to facilitate cue combination we introduce a gating operator based on the texturedness of the neighborhood at a pixel. Having obtained a local measure of how likely two nearby pixels are to belong to the same region, we use the spectral graph theoretic framework of normalized cuts to find partitions of the image into regions of coherent texture and brightness. Experimental results on a wide range of images are shown.
7 schema:editor Nf2daa21309834ddcaa83ab9a93143838
8 schema:genre chapter
9 schema:isAccessibleForFree true
10 schema:isPartOf Nc4f6f5bb2658480e9d1958323d3403c4
11 schema:keywords algorithm
12 analysis
13 applicability
14 brightness
15 coherent texture
16 combination
17 contours
18 cue combination
19 cues
20 cut
21 differences
22 disjoint regions
23 domain
24 domain of applicability
25 experimental results
26 framework
27 graph-theoretic framework
28 gray-scale images
29 image segmentation
30 images
31 local measures
32 measures
33 natural images
34 nearby pixels
35 neighborhood
36 operators
37 paper
38 partition
39 pixels
40 range
41 region
42 results
43 same region
44 segmentation
45 spectral graph theoretic framework
46 textons
47 texture
48 texture analysis
49 texture differences
50 texturedness
51 theoretic framework
52 untextured regions
53 wide range
54 schema:name Contour and Texture Analysis for Image Segmentation
55 schema:pagination 139-172
56 schema:productId N8989ce0d906d473ebd5eacc175df38db
57 N91c7b6e0f6dd409d895a0b41e3c4e58f
58 schema:publisher N08789812ea2e40c2978501ee14fda6ac
59 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046278747
60 https://doi.org/10.1007/978-1-4615-4413-5_9
61 schema:sdDatePublished 2022-12-01T06:46
62 schema:sdLicense https://scigraph.springernature.com/explorer/license/
63 schema:sdPublisher Nc26b2cbde11d4edcaebf16cd4243fa50
64 schema:url https://doi.org/10.1007/978-1-4615-4413-5_9
65 sgo:license sg:explorer/license/
66 sgo:sdDataset chapters
67 rdf:type schema:Chapter
68 N08789812ea2e40c2978501ee14fda6ac schema:name Springer Nature
69 rdf:type schema:Organisation
70 N1e083562bdd54cd3af8fce90b74eaded schema:familyName Boyer
71 schema:givenName Kim L.
72 rdf:type schema:Person
73 N6508cddb4aed41a1a04cca0aa7c6977f schema:familyName Sarkar
74 schema:givenName Sudeep
75 rdf:type schema:Person
76 N820685945b4d4981b597373814d4ef62 rdf:first sg:person.0632735744.68
77 rdf:rest Ndf600fcc40314903a4108936db3445f1
78 N8989ce0d906d473ebd5eacc175df38db schema:name doi
79 schema:value 10.1007/978-1-4615-4413-5_9
80 rdf:type schema:PropertyValue
81 N91c7b6e0f6dd409d895a0b41e3c4e58f schema:name dimensions_id
82 schema:value pub.1046278747
83 rdf:type schema:PropertyValue
84 N986a1af0db394ee0b4f23b4234300d42 rdf:first sg:person.016214030753.30
85 rdf:rest rdf:nil
86 Nc26b2cbde11d4edcaebf16cd4243fa50 schema:name Springer Nature - SN SciGraph project
87 rdf:type schema:Organization
88 Nc4f6f5bb2658480e9d1958323d3403c4 schema:isbn 978-1-4613-6986-8
89 978-1-4615-4413-5
90 schema:name Perceptual Organization for Artificial Vision Systems
91 rdf:type schema:Book
92 Nd37c7b89a0984347b7fa105006bd3a19 rdf:first sg:person.01364521761.84
93 rdf:rest N820685945b4d4981b597373814d4ef62
94 Ndf600fcc40314903a4108936db3445f1 rdf:first sg:person.016034550437.98
95 rdf:rest N986a1af0db394ee0b4f23b4234300d42
96 Nf2daa21309834ddcaa83ab9a93143838 rdf:first N1e083562bdd54cd3af8fce90b74eaded
97 rdf:rest Nf319567184d74d27ba14f4959a059d8e
98 Nf319567184d74d27ba14f4959a059d8e rdf:first N6508cddb4aed41a1a04cca0aa7c6977f
99 rdf:rest rdf:nil
100 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
101 schema:name Information and Computing Sciences
102 rdf:type schema:DefinedTerm
103 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
104 schema:name Artificial Intelligence and Image Processing
105 rdf:type schema:DefinedTerm
106 sg:person.01364521761.84 schema:affiliation grid-institutes:grid.30389.31
107 schema:familyName Malik
108 schema:givenName Jitendra
109 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01364521761.84
110 rdf:type schema:Person
111 sg:person.016034550437.98 schema:affiliation grid-institutes:grid.30389.31
112 schema:familyName Leung
113 schema:givenName Thomas
114 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016034550437.98
115 rdf:type schema:Person
116 sg:person.016214030753.30 schema:affiliation grid-institutes:grid.30389.31
117 schema:familyName Shi
118 schema:givenName Jianbo
119 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016214030753.30
120 rdf:type schema:Person
121 sg:person.0632735744.68 schema:affiliation grid-institutes:grid.30389.31
122 schema:familyName Belongie
123 schema:givenName Serge
124 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0632735744.68
125 rdf:type schema:Person
126 grid-institutes:grid.30389.31 schema:alternateName University of Califonia, Berkeley, USA
127 schema:name University of Califonia, Berkeley, USA
128 rdf:type schema:Organization
 




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


...