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Peer-Reviewed Academic JournalInternational Journal of Applied Methods in Electronics and Computers
ISSN: 3023-4409DOI Prefix: 10.58190/ijamec
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Pages: 1-6

A Comparative Evaluation of Well-known Feature Detectors and Descriptors

Şahin IŞIK
Kemal ÖZKAN
Publication DateJanuary 17, 2015
Volume / IssueVol. 3, No. 1 (pp. 1-6)
DOI Identifier10.18100/ijamec.60004
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Abstract

Comparison of feature detectors and descriptors and assessing their performance is very important in computer vision. In this study, we evaluate the performance of seven combination of well-known detectors and descriptors which are SIFT with SIFT, SURF with SURF, MSER with SIFT, BRISK with FREAK, BRISK with BRISK, ORB with ORB and FAST with BRIEF. The popular Oxford dataset is used in test stage. To compare the performance of each combination objectively, the effects of JPEG compression, zoom and rotation, blur, viewpoint and illumination variation have investigated in terms of precision and recall values. Upon inspecting the obtained results, it is observed that the combination of ORB with ORB and MSER with SIFT can be preferable almost in all possible situations when the precision and recall results are considered. Moreover, the speed of FAST with BRIEF is superior to others.
Keywords:Image matchingfeature detectorfeature descriptorsSIFTSURFBRIEFFASTBRISKORBMSER

Author Affiliations

  • Şahin IŞIK Eskisehir Osmangazi University, Turkey
  • Kemal ÖZKAN Eskisehir Osmangazi University, Turkey
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How to Cite This Article

IŞIK, Ş., ÖZKAN, K. (2015). A Comparative Evaluation of Well-known Feature Detectors and Descriptors. International Journal of Applied Methods in Electronics and Computers, 1-6. https://doi.org/10.18100/ijamec.60004