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An automated vision-based method to detect elephants for mitigation of human-elephant conflicts

机译:一种自动的基于视觉的方法来检测大象以减轻人与大象之间的冲突

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Human-elephant conflict is a frontline conservation issue in the world. The loss and fragmentation of elephant's habitat owing to the increased human encroachment leads to a notable conservation issue. It raises the need for a non-invasive and efficient solution for the mitigation of human-elephant conflicts. Consequently, deploying a vision based surveillance method in the real time environment can prove to be significantly useful to provide the warnings well in advance thereby reducing the human elephant conflict. In this paper, a method for the identification of elephant as an object using image processing is proposed. The method dynamically learns from the trained images with different backgrounds, lighting conditions. Further, it classifies the input image based on the features of color and texture. The outcomes demonstrate that the proposed method effectively deals with the detection of elephants in near and far distances, cluttered and occluded environment.
机译:人与大象的冲突是世界上最前沿的保护问题。由于人类入侵的增加,大象栖息地的丧失和破碎导致了一个显着的保护问题。因此,需要一种非侵入性的有效解决方案来减轻人与大象之间的冲突。因此,在实时环境中部署基于视觉的监视方法可以证明对提前提供警告非常有用,从而减少了人类的大象冲突。提出了一种利用图像处理识别大象为对象的方法。该方法从具有不同背景,光照条件的训练图像中动态学习。此外,它基于颜色和纹理的特征对输入图像进行分类。结果表明,所提出的方法有效地处理了在近距离和远距离,杂乱无章的环境中对大象的检测。

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