Affine versus projective transformation for SIFT and RANSAC image matching methods

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Image registration is a process of determining the geometrical transformation that aligns two or more images taken from different viewpoints and sensors at different times. Scale Invariant Feature Transform (SIFT) method has gained more popularity since it extracts the highest number of features and matching points compared to Speeded-Up Robust Feature (SURF) and Harris Corner Detector at little computational cost. In this paper, a combination of SIFT and Random Sample Consensus (RANSAC) is used to produce panoramic image. In order to reject outliers and estimate the transformation model, affine and projective transformations are used to study the best geometrical transformations methods to be used. The results shows that the projective transformation has a better performance in terms of accuracy.

Original languageEnglish
Title of host publicationIEEE 2015 International Conference on Signal and Image Processing Applications, ICSIPA 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages447-451
Number of pages5
ISBN (Electronic)9781479989966
DOIs
Publication statusPublished - 17 Feb 2016
Event4th IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2015 - Kuala Lumpur, Malaysia
Duration: 19 Oct 201521 Oct 2015

Publication series

NameIEEE 2015 International Conference on Signal and Image Processing Applications, ICSIPA 2015 - Proceedings

Other

Other4th IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2015
CountryMalaysia
CityKuala Lumpur
Period19/10/1521/10/15

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Signal Processing

Fingerprint Dive into the research topics of 'Affine versus projective transformation for SIFT and RANSAC image matching methods'. Together they form a unique fingerprint.

  • Cite this

    Redzuwan, R., Radzi, N. A. M., Din, N. M., & Mustafa, I. S. (2016). Affine versus projective transformation for SIFT and RANSAC image matching methods. In IEEE 2015 International Conference on Signal and Image Processing Applications, ICSIPA 2015 - Proceedings (pp. 447-451). [7412233] (IEEE 2015 International Conference on Signal and Image Processing Applications, ICSIPA 2015 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSIPA.2015.7412233