Evaluation of SIFT and SURF features in the songket recognition

Dominikus Willy, Ary Noviyanto, Aniati Murni Arymurthy

Research output: Contribution to conferencePaperpeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Pages393-396
Number of pages4
DOIs
Publication statusPublished - 1 Jan 2013
Event2013 5th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2013 - Bali, Indonesia
Duration: 28 Sep 201329 Sep 2013

Conference

Conference2013 5th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2013
CountryIndonesia
CityBali
Period28/09/1329/09/13

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