Image retrieval using colour features

dc.contributor.advisor Jin, Jesse en_US Seo, Jeng Won en_US 2022-03-16T15:14:22Z 2022-03-16T15:14:22Z 1996 en_US
dc.description.abstract With the significant outgrowth of hardware technology, the amount of pictorial information has increased remarkably. Due to this increase in image data, the need for an efficient indexing technology arises. In earlier retrieval systems, images are described using plain text and retrieval is based on the text description using conventional information retrieval techniques. These systems are good for retrieval abstract concepts captured in images. However, it suffers the problem of subjectiveness and manual entry of text description. To overcome these limitations content-based retrieval techniques using image features have been proposed. The main features used for image retrieval are shape, texture and colour. The purpose of our work is to develop an efficient content-based retrieval technique based on colour. Researchs on colour feature have shown very successful results. However, these techniques have been applied to the overall image content. The processing time for extracting colour features is another problem. In this paper, we propose three extensions to the basic colour histogram matching technique: (a) the use of hue value of HSI colour space; (b) the use of segmentation for object level; and (c) the use of clustering. en_US
dc.language English
dc.language.iso EN en_US
dc.publisher UNSW, Sydney en_US
dc.rights CC BY-NC-ND 3.0 en_US
dc.rights.uri en_US
dc.source Thesis Digitisation Program en_US
dc.subject.other Document imaging systems en_US
dc.subject.other Image processing en_US
dc.subject.other Imaging systems en_US
dc.subject.other Documents in optical storage en_US
dc.title Image retrieval using colour features en_US
dc.type Thesis en_US
dcterms.accessRights open access
dcterms.rightsHolder Seo, Jeng Won
dspace.entity.type Publication en_US
unsw.relation.faculty Engineering
unsw.relation.originalPublicationAffiliation Seo, Jeng Won, Computer Science & Engineering, Faculty of Engineering, UNSW en_US
unsw.relation.originalPublicationAffiliation Jin, Jesse , Computer Science & Engineering, Faculty of Engineering, UNSW en_US School of Computer Science and Engineering *
unsw.thesis.degreetype Masters Thesis en_US
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