Pre-processing Techniques to Improve the Efficiency of Video Identification for the Pygmy Bluetongue Lizard

Damian Tohl, Jimmy Li, C. Michael Bull

2015

Abstract

In the study of the endangered Pygmy Bluetongue Lizard, non-invasive photographic identification is preferred to the current invasive methods which can be unreliable and cruel. As the lizard is an endangered species, there are restrictions on its handling. The lizard is also in constant motion and it is therefore difficult to capture a good still image for identification purposes. Hence video capture is preferred as a number of images of the lizard at various positions and qualities can be collected in just a few seconds from which the best image can be selected for identification. With a large number of individual lizards in the database, matching a video sequence of images against each database image for identification will render the process very computationally inefficient. Moreover, a large portion of those images are non-identifiable due to motion and optical blur and different body curvature to the reference database image. In this paper, we propose a number of pre-processing techniques for pre-selecting the best image out of the video image sequence for identification. Using our proposed pre-selection techniques, it has been shown that the computational efficiency can be significantly improved.

References

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Paper Citation


in Harvard Style

Tohl D., Li J. and Bull C. (2015). Pre-processing Techniques to Improve the Efficiency of Video Identification for the Pygmy Bluetongue Lizard . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-089-5, pages 623-629. DOI: 10.5220/0005317306230629


in Bibtex Style

@conference{visapp15,
author={Damian Tohl and Jimmy Li and C. Michael Bull},
title={Pre-processing Techniques to Improve the Efficiency of Video Identification for the Pygmy Bluetongue Lizard},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={623-629},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005317306230629},
isbn={978-989-758-089-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)
TI - Pre-processing Techniques to Improve the Efficiency of Video Identification for the Pygmy Bluetongue Lizard
SN - 978-989-758-089-5
AU - Tohl D.
AU - Li J.
AU - Bull C.
PY - 2015
SP - 623
EP - 629
DO - 10.5220/0005317306230629