Image Registration Techniques Based on the Scale Invariant Feature Transform for Aerial Surveillance Images

Authors

  • Vaithiyanathan V
  • Divya Lakshmi K
  • Radha Rammohan S

Keywords:

local features, aerial surveillance images, image matching, affine invariance

Abstract

Aerial surveillance plays a vital role in continuous monitoring of areas where human intervention is of higher risk. Image registration is a process to bring several images of a scene to a single co-ordinate system. It is widely done using the local features extracted from the images. Local features of an aerial surveillance image is also used in several computer vision tasks such as scene matching, object identification and object tracking. The features identified must be repeatable across several transformations on the image.  This paper aims to find the most repeatable local feature from the existing state of art affine invariant features : Harris Affine, Hessian Affine. They are described using the Scale Invariant Feature Transform (SIFT). The dataset comprises aerial images captured from low altitude unmanned aerial vehicles using thermal and visual sensors. The ground truth between the images of a scene is estimated manually using control points, in the form of a homograph matrix. The repeatability of the various features are estimated using the ground truth estimated. The Hessian Affine feature outperforms in performance compared to the other affine invariant feature detector making it a potential candidate for the various computer vision tasks on aerial surveillance images.

References

Lisa Gottesfield Brown, " A study of image registeration techniques", ACM Computing Surveys, vol. 24, no. 4, pp. 325-376, December 1992.

Krystian Mikolajczyk, and Cordelia Schmid, " Scale & Affine Invariant Interest Point Detectors", International Journal of Computer Vision, vol. 60, no. 1, pp. 63-86, October 2004.

Lowe, D. G., "Distinctive Image Features from Scale-Invariant Keypoints", International Journal of Computer Vision, vol. 60, no. 2, pp. 91-110, November 2004.

Krystian Mikolajczyk, and Cordelia Schmid, "A performance evaluation of local descriptors", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 10, no. 27, pp. 1615-1630, October 2005.

Saeed Yahyanejad, and Bernhard Rinner, "A fast and mobile system for registration of low-altitude visual and thermal aerial images using multiple small-scale UAVs", ISPRS Journal of Photogrammetry and Remote Sensing, vol. 104, pp. 189-202, June 2015.

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How to Cite

V, V., K, D. L., & S, R. R. (2016). Image Registration Techniques Based on the Scale Invariant Feature Transform for Aerial Surveillance Images. Asian Journal of Computer and Information Systems, 4(1). Retrieved from https://ajouronline.com/index.php/AJCIS/article/view/3620