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Copyright 2015 SCITEPRESS (Science and Technology Publications, Lda.). Published version of the paper reproduced here with permission from the publisherIn the study of the endangered Pygmy Bluetongue Lizard, non-invasive photographic identification is\udpreferred to the current invasive methods which can be unreliable and cruel. As the lizard is an endangered\udspecies, there are restrictions on its handling. The lizard is also in constant motion and it is therefore\uddifficult to capture a good still image for identification purposes. Hence video capture is preferred as a\udnumber of images of the lizard at various positions and qualities can be collected in just a few seconds from\udwhich the best image can be selected for identification. With a large number of individual lizards in the\uddatabase, matching a video sequence of images against each database image for identification will render\udthe process very computationally inefficient. Moreover, a large portion of those images are non-identifiable\uddue to motion and optical blur and different body curvature to the reference database image. In this paper,\udwe propose a number of pre-processing techniques for pre-selecting the best image out of the video image\udsequence for identification. Using our proposed pre-selection techniques, it has been shown that the\udcomputational efficiency can be significantly improved

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