DocumentCode :
3543072
Title :
Evaluation of SIFT and SURF features in the songket recognition
Author :
Willy, Dominikus ; Noviyanto, Ary ; Arymurthy, Aniati Murni
Author_Institution :
Fac. of Comput. Sci., Univ. Indonesia, Depok, Indonesia
fYear :
2013
fDate :
28-29 Sept. 2013
Firstpage :
393
Lastpage :
396
Abstract :
The songket recognition is a challenging task. The SIFT and SURF, which are feature descriptors, are considered as potential features for pattern matching. The Songket is a special pattern originally from Indonesia; The Songket Palembang is used in this research. One motif in the Songket Palembang may has several different basic patterns. The matching scores, i.e., distance measure and number of keypoint, are evaluated corresponding with the SIFT and SURF method. SIFT method has been better than SURF method, but SURF has been extremely faster than SIFT.
Keywords :
fabrics; feature extraction; image recognition; pattern matching; Indonesia; SIFT; SURF; Songket Palembang; Songket recognition; distance measure; feature descriptor; matching scores; pattern matching; Accuracy; Computer science; Feature extraction; Noise; Pattern matching; Robustness; Transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computer Science and Information Systems (ICACSIS), 2013 International Conference on
Conference_Location :
Bali
Type :
conf
DOI :
10.1109/ICACSIS.2013.6761607
Filename :
6761607
Link To Document :
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