Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/52458
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dc.contributor.authorJennisa Areeyapinanen_US
dc.contributor.authorPizzanu Kanongchaiyosen_US
dc.contributor.authorAram Kawewongen_US
dc.date.accessioned2018-09-04T09:25:31Z-
dc.date.available2018-09-04T09:25:31Z-
dc.date.issued2013-01-01en_US
dc.identifier.other2-s2.0-84893338812en_US
dc.identifier.other10.1109/CultureComputing.2013.14en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84893338812&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/52458-
dc.description.abstractWe present a method for Khon image retrieval using multi-descriptors. Khon is an ancient Thai cultural heritage that is very well-known from its gorgeous costumes and dance. Khon image retrieval can be adopted in various fields of work to preserve Thai culture and tradition. However, it is not trivial because of its complex and duplicated pattern caused by unique Thai line art. Thus, we integrate a Scale-invariant feature transform (SIFT) and Critical Point Filters (CPFs) to achieve accurate and fast Khon image retrieval. SIFT is used for details image such as Khon image. In order to reduce the time complexity for extracting key points using SIFT, we apply CPF which filter only the critical pixel of the image. From the experiment, our method can reduce computation time by 43.3% from SIFT and nearly 100% from CPF. Moreover, our method is preserve efficiency. © 2013 IEEE.en_US
dc.subjectComputer Scienceen_US
dc.titleUsing multi-descriptors for khon image retrievalen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleProceedings - 2013 International Conference on Culture and Computing, Culture and Computing 2013en_US
article.stream.affiliationsChulalongkorn Universityen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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