Evaluation of SIFT and SURF features in the songket recognition

Dominikus Willy; Ary Noviyanto; Aniati Murni Arymurthy

doi:10.1109/ICACSIS.2013.6761607

Evaluation of SIFT and SURF features in the songket recognition

Dominikus Willy, Ary Noviyanto, Aniati Murni Arymurthy

Faculty of Computer Science

Research output: Contribution to conference › Paper › peer-review

5 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 language	English
Pages	393-396
Number of pages	4
DOIs	https://doi.org/10.1109/ICACSIS.2013.6761607
Publication status	Published - 2013
Event	2013 5th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2013 - Bali, Indonesia Duration: 28 Sept 2013 → 29 Sept 2013

Conference

Conference	2013 5th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2013
Country/Territory	Indonesia
City	Bali
Period	28/09/13 → 29/09/13

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10.1109/ICACSIS.2013.6761607

Cite this

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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.",

author = "Dominikus Willy and Ary Noviyanto and Arymurthy, {Aniati Murni}",

year = "2013",

doi = "10.1109/ICACSIS.2013.6761607",

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AU - Noviyanto, Ary

AU - Arymurthy, Aniati Murni

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DO - 10.1109/ICACSIS.2013.6761607

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T2 - 2013 5th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2013

Y2 - 28 September 2013 through 29 September 2013

ER -

Evaluation of SIFT and SURF features in the songket recognition

Abstract

Conference

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