Scale Invariant Feature Transform using oriented pattern

Author

Daneshvar, Mohammad Baghery ; Babaie-Zadeh, Massoud ; Ghorshi, Seyed

Author_Institution

Sch. of Sci. & Eng., Sharif Univ. of Technol., Kish Island, Iran

fYear

2014

fDate

4-7 May 2014

Firstpage

1

Lastpage

5

Abstract

Image matching plays an important role in many aspects of computer vision. Our proposed method is based on Scale Invariant Feature Transform (SIFT) which is one of the popular image matching methods. The main ideas behind our method are removing the excess keypoints, adding oriented patterns to descriptor, and decreasing the size of the descriptors. By doing these changes to SIFT, we would have oriented patterns of keypoints. In addition, the numbers of keypoints have been reduced and the places of keypoints would be selected more accurately, and also the size of the descriptors has been reduced.

Keywords

computer vision; image matching; SIFT; computer vision; image matching methods; oriented pattern; scale invariant feature transform; Computer vision; Detectors; Feature extraction; Histograms; Image edge detection; Image matching; Lighting; Image matching; descriptor; feature extraction; keypoint; oriented pattern;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering (CCECE), 2014 IEEE 27th Canadian Conference on

Conference_Location

Toronto, ON

ISSN

0840-7789

Print_ISBN

978-1-4799-3099-9

Type

conf

DOI

10.1109/CCECE.2014.6900952

Filename

6900952