Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/52458
Title: Using multi-descriptors for khon image retrieval
Authors: Jennisa Areeyapinan
Pizzanu Kanongchaiyos
Aram Kawewong
Authors: Jennisa Areeyapinan
Pizzanu Kanongchaiyos
Aram Kawewong
Keywords: Computer Science
Issue Date: 1-Jan-2013
Abstract: We 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.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84893338812&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/52458
Appears in Collections:CMUL: Journal Articles

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