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首页> 外文会议>International Conference on Computer Vision Theory and Applications >Pre-processing Techniques to Improve the Efficiency of Video Identification for the Pygmy Bluetongue Lizard
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Pre-processing Techniques to Improve the Efficiency of Video Identification for the Pygmy Bluetongue Lizard

机译：提高Pygmy BlueTongue蜥蜴视频识别效率的预处理技术

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摘要

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.
机译：在濒危侏儒BlueTongue蜥蜴的研究中，无侵入式摄影鉴定对于目前的侵入性方法是不可靠和残忍的。随着蜥蜴是一种濒危物种，其处理有限。蜥蜴也处于恒定运动，因此难以捕获良好的静止图像以进行识别目的。因此，视频捕获是优选的，因为可以在各个位置的蜥蜴的许多图像，并且可以仅在几秒钟内收集质量，从中可以选择最佳图像以用于识别。在数据库中具有大量单独的蜥蜴，将图像的视频序列与每个数据库图像匹配以进行识别，将呈现非常计算效率低下的过程。此外，由于运动和光学模糊和不同的身体曲率与参考数据库图像不同，这些图像的大部分是不可识别的。在本文中，我们提出了许多预处理技术，用于预先选择从视频图像序列中预先选择最佳图像以进行识别。使用我们所提出的预选技术，已经表明可以显着提高计算效率。

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