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Content-based image retrieval

Content-based image retrieval, also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases (see this survey for a scientific overview of the CBIR field).…

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Overview

Comparison with metadata searching

History

Technical progress

Techniques

Content comparison using image distance measures

Vulnerabilities, attacks and defenses

Image retrieval evaluation

Image retrieval in CBIR system simultaneously by different techniques

Applications

Relevant research papers

  • JISC Joint Information Systems Committee

Advanced semantic analysis

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Map overview Semantic statistics

Content-based image retrieval

Nodes56
Edges55
Triples187
Avg. degree1.96
Density0.035714
Components1

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Content-based image retrieval

Top relations

related to Relevant research papers · 154
Content-based image retrieval → Accurate Image Annotation, Adaptively Browsing Image Databases, Advances, Alexis, Algorithm, Amsaleg, An Interactive Face Retrieval, Arandjelovic, Ardizzoni, Art, Automatic Face Recognition, Automatic Linguistic Indexing, Automatic Video Content Indexing, Bartolini, Berg, Browsing Engine, Challenges, Ciaccia, Conceptual Approach, Content
related to Content comparison using image distance measures · 7
Content-based image retrieval → An, As, For, Many, Search, Similarity Models, The
related to history · 4
Content-based image retrieval → Japanese Electrotechnical Laboratory, Since, The, Toshikazu Kato

Important terminology Word statistics

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Important terminology

image images cbir search query retrieval content texture systems based content-based example shape also techniques user methods may developed distance

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
keywordsinstance ofmeans that the search analyzes the contents of the image rather than the metadata0.80text
tagsinstance ofmeans that the search analyzes the contents of the image rather than the metadata0.80text
or descriptions associated with the imageinstance ofmeans that the search analyzes the contents of the image rather than the metadata0.80text
statisticsinstance ofand algorithms that are used originate from fields0.80text
pattern recognitioninstance ofand algorithms that are used originate from fields0.80text
signal processinginstance ofand algorithms that are used originate from fields0.80text
and computer vision..mw-parser-output .vanchorinstance ofand algorithms that are used originate from fields0.80text
colorinstance ofAn image distance measure compares the similarity of two images in various dimensions0.80text
textureinstance ofAn image distance measure compares the similarity of two images in various dimensions0.80text
shapeinstance ofAn image distance measure compares the similarity of two images in various dimensions0.80text
and othersinstance ofAn image distance measure compares the similarity of two images in various dimensions0.80text
silkyinstance ofThe problem is in identifying patterns of co-pixel variation and associating them with particular classes of textures0.80text

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