DocumentCode :
651999
Title :
Using Multi-descriptors for Khon Image Retrieval
Author :
Areeyapinan, Jennisa ; Kanongchaiyos, Pizzanu ; Kawewong, Aram
Author_Institution :
Comput. Eng., Chulalongkorn Univ., Bangkok, Thailand
fYear :
2013
fDate :
16-18 Sept. 2013
Firstpage :
33
Lastpage :
38
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.
Keywords :
art; feature extraction; filtering theory; history; image retrieval; CPF; Khon image retrieval; SIFT; Thai culture; Thai line art; Thai tradition; ancient Thai cultural heritage; critical point filters; image pixel; key points exraction; multidescriptors; scale-invariant feature transform; time complexity; Accuracy; Feature extraction; Image color analysis; Image retrieval; Shape; Khon; critical point filters; image retrieval; scale-invariant feature transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Culture and Computing (Culture Computing), 2013 International Conference on
Conference_Location :
Kyoto
Type :
conf
DOI :
10.1109/CultureComputing.2013.14
Filename :
6680327
Link To Document :
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