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dc.contributor.authorLiew, Alan Wee-Chung
dc.contributor.authorLaw, Ngai-Fong
dc.contributor.editorMehdi Khosrow-Pour
dc.date.accessioned2018-01-10T23:41:38Z
dc.date.available2018-01-10T23:41:38Z
dc.date.issued2009
dc.date.modified2014-02-07T06:02:27Z
dc.identifier.isbn9781605660264en_US
dc.identifier.doi10.4018/978-1-60566-026-4.ch121en_US
dc.identifier.urihttp://hdl.handle.net/10072/28121
dc.description.abstractWith the rapid growth of Internet and multimedia systems, the use of visual information has increased enormously, such that indexing and retrieval techniques have become important. Historically, images are usually manually annotated with metadata such as captions or keywords (Chang & Hsu, 1992). Image retrieval is then performed by searching images with similar keywords. However, the keywords used may differ from one person to another. Also, many keywords can be used for describing the same image. Consequently, retrieval results are often inconsistent and unreliable. Due to these limitations, there is a growing interest in content-based image retrieval (CBIR). These techniques extract meaningful information or features from an image so that images can be classified and retrieved automatically based on their contents. Existing image retrieval systems such as QBIC and Virage extract the so-called low-level features such as color, texture and shape from an image in the spatial domain for indexing. Low-level features sometimes fail to represent high level semantic image features as they are subjective and depend greatly upon user preferences. To bridge the gap, a top-down retrieval approach involving high level knowledge can complement these low-level features. This articles deals with various aspects of CBIR. This includes bottom-up feature- based image retrieval in both the spatial and compressed domains, as well as top-down task-based image retrieval using prior knowledge.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_US
dc.languageEnglishen_US
dc.language.isoen_US
dc.publisherInformation Science Reference, IGI Global Publishingen_US
dc.publisher.placeUnited Statesen_US
dc.publisher.urihttp://dx.doi.org/10.4018/978-1-60566-026-4en_US
dc.relation.ispartofbooktitleEncyclopedia of Information Science and Technologyen_US
dc.relation.ispartofchapter39en_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofpagefrom744en_US
dc.relation.ispartofpageto749en_US
dc.relation.ispartofedition2en_US
dc.relation.ispartofvolume2en_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchImage Processingen_US
dc.subject.fieldofresearchPattern Recognition and Data Miningen_US
dc.subject.fieldofresearchcode080106en_US
dc.subject.fieldofresearchcode080109en_US
dc.titleContent-Based Image Retrievalen_US
dc.typeBook chapteren_US
dc.type.descriptionB1 - Book Chapters (HERDC)en_US
dc.type.codeB - Book Chaptersen_US
gro.facultyGriffith Sciences, School of Information and Communication Technologyen_US
gro.date.issued2009
gro.hasfulltextNo Full Text


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