Improved roational matching of SIFT and SURF
Scale-Invariant Feature Transform(SIFT) and Speeded-Up Robust Feature(SURF) are common techniques used for extracting robust features that can be used to perform matching between different viewpoints of scenes. Both methods basically involve three main stages, which are feature extraction, orientati...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Conference or Workshop Item |
| Published: |
2012
|
| Online Access: | http://eprints.utm.my/id/eprint/34107/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
my.utm.34107 |
|---|---|
| record_format |
eprints |
| spelling |
my.utm.341072017-09-10T05:54:31Z http://eprints.utm.my/id/eprint/34107/ Improved roational matching of SIFT and SURF Goh, K. M. Mohd. Mokji, Musa Scale-Invariant Feature Transform(SIFT) and Speeded-Up Robust Feature(SURF) are common techniques used for extracting robust features that can be used to perform matching between different viewpoints of scenes. Both methods basically involve three main stages, which are feature extraction, orientation assignment and feature descriptor extraction for matching. SURF is computation efficient compared to SIFT because the integral image is used for the convolutions to reduce computation time. However, both methods also do not focus much on the technique of matching. This paper introduces a method which can help to improve the rotational matching performance in term of accuracy by establishing a decision matrix and an approximated rotational angle within two corresponding images. The proposed method generally improved the matching rate around 10% to 20% in terms of accuracy. 2012 Conference or Workshop Item PeerReviewed Goh, K. M. and Mohd. Mokji, Musa (2012) Improved roational matching of SIFT and SURF. In: 4th International Confernece on Digital Image Processing (ICDIP 2012). |
| institution |
Universiti Teknologi Malaysia |
| building |
UTM Library |
| collection |
Institutional Repository |
| continent |
Asia |
| country |
Malaysia |
| content_provider |
Universiti Teknologi Malaysia |
| content_source |
UTM Institutional Repository |
| url_provider |
http://eprints.utm.my/ |
| description |
Scale-Invariant Feature Transform(SIFT) and Speeded-Up Robust Feature(SURF) are common techniques used for extracting robust features that can be used to perform matching between different viewpoints of scenes. Both methods basically involve three main stages, which are feature extraction, orientation assignment and feature descriptor extraction for matching. SURF is computation efficient compared to SIFT because the integral image is used for the convolutions to reduce computation time. However, both methods also do not focus much on the technique of matching. This paper introduces a method which can help to improve the rotational matching performance in term of accuracy by establishing a decision matrix and an approximated rotational angle within two corresponding images. The proposed method generally improved the matching rate around 10% to 20% in terms of accuracy. |
| format |
Conference or Workshop Item |
| author |
Goh, K. M. Mohd. Mokji, Musa |
| spellingShingle |
Goh, K. M. Mohd. Mokji, Musa Improved roational matching of SIFT and SURF |
| author_facet |
Goh, K. M. Mohd. Mokji, Musa |
| author_sort |
Goh, K. M. |
| title |
Improved roational matching of SIFT and SURF |
| title_short |
Improved roational matching of SIFT and SURF |
| title_full |
Improved roational matching of SIFT and SURF |
| title_fullStr |
Improved roational matching of SIFT and SURF |
| title_full_unstemmed |
Improved roational matching of SIFT and SURF |
| title_sort |
improved roational matching of sift and surf |
| publishDate |
2012 |
| url |
http://eprints.utm.my/id/eprint/34107/ |
| _version_ |
1643649514593058816 |
| score |
13.211869 |