Efficient NCC-Based Image Matching Based on Novel Hierarchical Bounds View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2009

AUTHORS

Shou-Der Wei , Wei-Hau Pan , Shang-Hong Lai

ABSTRACT

In this paper, we propose a fast image matching algorithm based on the normalized cross correlation (NCC) by applying the winner-update strategy in conjunction with the novel hierarchical bounds of cross correlation. We derive a novel upper bound for the cross-correlation of image matching based on the lower bound of sum of square difference (SSD), which is derived in the Walsh-Hadamard domain because of its nice energy packing property. Applying this upper bound with the winner update search strategy can skip unnecessary calculation, thus significantly reducing the computational burden of NCC-based pattern matching. Experimental results show the proposed algorithm is very efficient for NCC-based image matching under different lighting conditions and noise levels. More... »

PAGES

807-815

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-10467-1_71

DOI

http://dx.doi.org/10.1007/978-3-642-10467-1_71

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1041070731


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": "Department of Computer Science and Information Engineering, Hungkuang University, Taichung, Taiwan", 
          "id": "http://www.grid.ac/institutes/grid.411432.1", 
          "name": [
            "Department of Computer Science and Information Engineering, Hungkuang University, Taichung, Taiwan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wei", 
        "givenName": "Shou-Der", 
        "id": "sg:person.013224413773.06", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013224413773.06"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan", 
          "id": "http://www.grid.ac/institutes/grid.38348.34", 
          "name": [
            "Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Pan", 
        "givenName": "Wei-Hau", 
        "id": "sg:person.010476750713.22", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010476750713.22"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan", 
          "id": "http://www.grid.ac/institutes/grid.38348.34", 
          "name": [
            "Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lai", 
        "givenName": "Shang-Hong", 
        "id": "sg:person.010301330015.11", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010301330015.11"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2009", 
    "datePublishedReg": "2009-01-01", 
    "description": "In this paper, we propose a fast image matching algorithm based on the normalized cross correlation (NCC) by applying the winner-update strategy in conjunction with the novel hierarchical bounds of cross correlation. We derive a novel upper bound for the cross-correlation of image matching based on the lower bound of sum of square difference (SSD), which is derived in the Walsh-Hadamard domain because of its nice energy packing property. Applying this upper bound with the winner update search strategy can skip unnecessary calculation, thus significantly reducing the computational burden of NCC-based pattern matching. Experimental results show the proposed algorithm is very efficient for NCC-based image matching under different lighting conditions and noise levels.", 
    "editor": [
      {
        "familyName": "Muneesawang", 
        "givenName": "Paisarn", 
        "type": "Person"
      }, 
      {
        "familyName": "Wu", 
        "givenName": "Feng", 
        "type": "Person"
      }, 
      {
        "familyName": "Kumazawa", 
        "givenName": "Itsuo", 
        "type": "Person"
      }, 
      {
        "familyName": "Roeksabutr", 
        "givenName": "Athikom", 
        "type": "Person"
      }, 
      {
        "familyName": "Liao", 
        "givenName": "Mark", 
        "type": "Person"
      }, 
      {
        "familyName": "Tang", 
        "givenName": "Xiaoou", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-642-10467-1_71", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-642-10466-4", 
        "978-3-642-10467-1"
      ], 
      "name": "Advances in Multimedia Information Processing - PCM 2009", 
      "type": "Book"
    }, 
    "keywords": [
      "normalized cross correlation", 
      "image matching", 
      "winner-update strategy", 
      "fast image matching algorithm", 
      "Walsh-Hadamard domain", 
      "image matching algorithm", 
      "different lighting conditions", 
      "matching algorithm", 
      "cross correlation", 
      "pattern matching", 
      "computational burden", 
      "unnecessary calculations", 
      "lighting conditions", 
      "matching", 
      "algorithm", 
      "experimental results", 
      "search strategy", 
      "noise level", 
      "bounds", 
      "square difference", 
      "images", 
      "domain", 
      "strategies", 
      "sum", 
      "results", 
      "conjunction", 
      "burden", 
      "correlation", 
      "calculations", 
      "properties", 
      "levels", 
      "energy", 
      "conditions", 
      "differences", 
      "paper", 
      "novel hierarchical bounds", 
      "hierarchical bounds", 
      "nice energy", 
      "winner update search strategy", 
      "update search strategy", 
      "NCC-based pattern matching", 
      "NCC-based image", 
      "Efficient NCC-Based Image Matching", 
      "NCC-Based Image Matching"
    ], 
    "name": "Efficient NCC-Based Image Matching Based on Novel Hierarchical Bounds", 
    "pagination": "807-815", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1041070731"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-642-10467-1_71"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-642-10467-1_71", 
      "https://app.dimensions.ai/details/publication/pub.1041070731"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2021-12-01T19:58", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20211201/entities/gbq_results/chapter/chapter_171.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-3-642-10467-1_71"
  }
]
 

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.10.1007/978-3-642-10467-1_71'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-10467-1_71'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-10467-1_71'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-10467-1_71'


 

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

146 TRIPLES      23 PREDICATES      70 URIs      63 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-642-10467-1_71 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author Nf3ffc367be2b4faf9a5c0364433a5cc8
4 schema:datePublished 2009
5 schema:datePublishedReg 2009-01-01
6 schema:description In this paper, we propose a fast image matching algorithm based on the normalized cross correlation (NCC) by applying the winner-update strategy in conjunction with the novel hierarchical bounds of cross correlation. We derive a novel upper bound for the cross-correlation of image matching based on the lower bound of sum of square difference (SSD), which is derived in the Walsh-Hadamard domain because of its nice energy packing property. Applying this upper bound with the winner update search strategy can skip unnecessary calculation, thus significantly reducing the computational burden of NCC-based pattern matching. Experimental results show the proposed algorithm is very efficient for NCC-based image matching under different lighting conditions and noise levels.
7 schema:editor N86327fd5dd634047b8652494ae553074
8 schema:genre chapter
9 schema:inLanguage en
10 schema:isAccessibleForFree false
11 schema:isPartOf Nd1bb8a990a0b4303b5a9151f4f2c800e
12 schema:keywords Efficient NCC-Based Image Matching
13 NCC-Based Image Matching
14 NCC-based image
15 NCC-based pattern matching
16 Walsh-Hadamard domain
17 algorithm
18 bounds
19 burden
20 calculations
21 computational burden
22 conditions
23 conjunction
24 correlation
25 cross correlation
26 differences
27 different lighting conditions
28 domain
29 energy
30 experimental results
31 fast image matching algorithm
32 hierarchical bounds
33 image matching
34 image matching algorithm
35 images
36 levels
37 lighting conditions
38 matching
39 matching algorithm
40 nice energy
41 noise level
42 normalized cross correlation
43 novel hierarchical bounds
44 paper
45 pattern matching
46 properties
47 results
48 search strategy
49 square difference
50 strategies
51 sum
52 unnecessary calculations
53 update search strategy
54 winner update search strategy
55 winner-update strategy
56 schema:name Efficient NCC-Based Image Matching Based on Novel Hierarchical Bounds
57 schema:pagination 807-815
58 schema:productId N3b7d2ea39b8d4db6a5bdd836b7121f19
59 Nc4b65e4ffdfb4f89b700f5cad9d3c570
60 schema:publisher Nf1070bb915f4478695cc15bafd8a75c7
61 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041070731
62 https://doi.org/10.1007/978-3-642-10467-1_71
63 schema:sdDatePublished 2021-12-01T19:58
64 schema:sdLicense https://scigraph.springernature.com/explorer/license/
65 schema:sdPublisher Na36906ccdb7e44a98f0fe71c8af9d0b0
66 schema:url https://doi.org/10.1007/978-3-642-10467-1_71
67 sgo:license sg:explorer/license/
68 sgo:sdDataset chapters
69 rdf:type schema:Chapter
70 N0fb165daf14b4c78ae990edaeab799a1 rdf:first N23ddc70817af4bcdbffaa7d55c24e12b
71 rdf:rest N850239fd6587441e9ce20152cde99cc7
72 N1d1ac11f941c4712b27fd1fad19af6f5 schema:familyName Muneesawang
73 schema:givenName Paisarn
74 rdf:type schema:Person
75 N23ddc70817af4bcdbffaa7d55c24e12b schema:familyName Kumazawa
76 schema:givenName Itsuo
77 rdf:type schema:Person
78 N255c5ef63ba24e4f87b99b819bb243c7 schema:familyName Roeksabutr
79 schema:givenName Athikom
80 rdf:type schema:Person
81 N30ec27715ab049f1a013cf81fc46b2c7 rdf:first Ne3dc7df6219e4d6b97a64d75b6203e67
82 rdf:rest N847734d8c65740d3ab2a373cac15325d
83 N3607c3024e6349a4a10a6130b4102b2b schema:familyName Tang
84 schema:givenName Xiaoou
85 rdf:type schema:Person
86 N3b7d2ea39b8d4db6a5bdd836b7121f19 schema:name doi
87 schema:value 10.1007/978-3-642-10467-1_71
88 rdf:type schema:PropertyValue
89 N6ecd4d206c5c4d63bfb671df858ab47d rdf:first sg:person.010476750713.22
90 rdf:rest Nd883e3083aa04240ab37ea083b41b567
91 N847734d8c65740d3ab2a373cac15325d rdf:first N3607c3024e6349a4a10a6130b4102b2b
92 rdf:rest rdf:nil
93 N850239fd6587441e9ce20152cde99cc7 rdf:first N255c5ef63ba24e4f87b99b819bb243c7
94 rdf:rest N30ec27715ab049f1a013cf81fc46b2c7
95 N86327fd5dd634047b8652494ae553074 rdf:first N1d1ac11f941c4712b27fd1fad19af6f5
96 rdf:rest Nbe10c3ac2d1e4453889eb72d38d3bede
97 Na36906ccdb7e44a98f0fe71c8af9d0b0 schema:name Springer Nature - SN SciGraph project
98 rdf:type schema:Organization
99 Nbe10c3ac2d1e4453889eb72d38d3bede rdf:first Ne01e7d20d0fc469c90b7a3f6592b7745
100 rdf:rest N0fb165daf14b4c78ae990edaeab799a1
101 Nc4b65e4ffdfb4f89b700f5cad9d3c570 schema:name dimensions_id
102 schema:value pub.1041070731
103 rdf:type schema:PropertyValue
104 Nd1bb8a990a0b4303b5a9151f4f2c800e schema:isbn 978-3-642-10466-4
105 978-3-642-10467-1
106 schema:name Advances in Multimedia Information Processing - PCM 2009
107 rdf:type schema:Book
108 Nd883e3083aa04240ab37ea083b41b567 rdf:first sg:person.010301330015.11
109 rdf:rest rdf:nil
110 Ne01e7d20d0fc469c90b7a3f6592b7745 schema:familyName Wu
111 schema:givenName Feng
112 rdf:type schema:Person
113 Ne3dc7df6219e4d6b97a64d75b6203e67 schema:familyName Liao
114 schema:givenName Mark
115 rdf:type schema:Person
116 Nf1070bb915f4478695cc15bafd8a75c7 schema:name Springer Nature
117 rdf:type schema:Organisation
118 Nf3ffc367be2b4faf9a5c0364433a5cc8 rdf:first sg:person.013224413773.06
119 rdf:rest N6ecd4d206c5c4d63bfb671df858ab47d
120 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
121 schema:name Information and Computing Sciences
122 rdf:type schema:DefinedTerm
123 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
124 schema:name Artificial Intelligence and Image Processing
125 rdf:type schema:DefinedTerm
126 sg:person.010301330015.11 schema:affiliation grid-institutes:grid.38348.34
127 schema:familyName Lai
128 schema:givenName Shang-Hong
129 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010301330015.11
130 rdf:type schema:Person
131 sg:person.010476750713.22 schema:affiliation grid-institutes:grid.38348.34
132 schema:familyName Pan
133 schema:givenName Wei-Hau
134 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010476750713.22
135 rdf:type schema:Person
136 sg:person.013224413773.06 schema:affiliation grid-institutes:grid.411432.1
137 schema:familyName Wei
138 schema:givenName Shou-Der
139 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013224413773.06
140 rdf:type schema:Person
141 grid-institutes:grid.38348.34 schema:alternateName Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan
142 schema:name Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan
143 rdf:type schema:Organization
144 grid-institutes:grid.411432.1 schema:alternateName Department of Computer Science and Information Engineering, Hungkuang University, Taichung, Taiwan
145 schema:name Department of Computer Science and Information Engineering, Hungkuang University, Taichung, Taiwan
146 rdf:type schema:Organization
 




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


...