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