Unsupervised region of intrest detection using fast and surf

Authors

Abass Olaode, University of WollongongFollow
Golshah Naghdy, University of WollongongFollow
Catherine Todd, University of Wollongong in DubaiFollow

RIS ID

107341

Publication Details

A. A. Olaode, G. Naghdy & C. A. Todd, "Unsupervised region of intrest detection using fast and surf," Computer Science & Information Technology, vol. 5, (4) pp. 63-72, 2015.

Abstract

The determination of Region-of-Interest has been re cognised as an important means by which unimportant image content can be identified and exc luded during image compression or image modelling, however existing Region-of-Interest dete ction methods are computationally expensive thus are mostly unsuitable for managing l arge number of images and the compression of images especially for real-time video applicatio ns. This paper therefore proposes an unsupervised algorithm that takes advantage of the high computation speed being offered by Speeded-Up Robust Features (SURF) and Features from Accelerated Segment Test (FAST) to achieve fast and efficient Region-of-Interest detec tion.