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Efficient rotation invariant texture features for content-based image retrieval
Fountain, SR; Tan, TN
AbstractAn efficient approach to the extraction of rotation invariant texture features is presented. Histograms of intensity gradient directions are compiled. Rotation invariant features are extracted by taking the Fourier expansion of the histogram. The method is applied to image database annotation and content based retrieval. With a database of over 400 randomly rotated images all textures are correctly identified on the return of two classifications. On presentation of a texture to the image retrieval system nine out of ten images returned from the search are of the same texture as the query image. Its simplicity and accuracy render the method highly suited to applications such as content-based image retrieval. The method requires no human intervention. Extensive experimental results are included to demonstrate the performance of the method in texture classification and content-based retrieval. (C) 1998 Pattern Recognition Society, Published by Elsevier Science Ltd. All rights reserved.
KeywordImage Database Rotation Invariance Content-based Retrieval Texture Analysis
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000076088700014
Citation statistics
Document Type期刊论文
Affiliation1.Univ Reading, Dept Comp Sci, Computat Vis Grp, Reading G6 6AY, Berks, England
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Fountain, SR,Tan, TN. Efficient rotation invariant texture features for content-based image retrieval[J]. PATTERN RECOGNITION,1998,31(11):1725-1732.
APA Fountain, SR,&Tan, TN.(1998).Efficient rotation invariant texture features for content-based image retrieval.PATTERN RECOGNITION,31(11),1725-1732.
MLA Fountain, SR,et al."Efficient rotation invariant texture features for content-based image retrieval".PATTERN RECOGNITION 31.11(1998):1725-1732.
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