基于数字图像处理的野生动物威胁预警系统

Raji C.G, Fathima Safa, Jishana P, Mohammed Adhil
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引用次数: 1

摘要

事实证明,在人类流动性高的地方,野生动物的渗透对人类和动物都是危险的。如果人们没有认出正在接近的野生动物,就可能导致直接攻击。由于它们的体型和运动方式,对野生动物的监测和监视是具有挑战性的。此外,识别被拍摄的物种也是一项重要的任务。大象、老虎和猴子对人类构成严重威胁,它们需要很长时间才能恢复。由于人与动物之间的相互作用可能对两种物种都有害,因此连续帧差分使得识别视频中的移动物体成为可能。利用这些特征可以识别运动物体。人与动物之间的互动可能是危险的。该系统基于数字图像处理、卷积神经网络和背景减法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Early Warning System from Threat of Wild Animals using Digital Image Processing
Wildlife infiltration in places with high human mobility has been proven to be dangerous for both humans and animals. If people fail to recognize an approaching wild animal, it may result in a direct attack. Due to their size and style of movement, monitoring and surveillance of wild animals is challenging. Additionally, it is a significant task to identify the species that were photographed. Elephants, tigers, and monkeys pose a serious threat to humans, and it will take a very long time for them to recover. Because interactions between humans and animals can be harmful to both species, successive frame differencing makes it possible to identify moving objects in videos. By utilizing the traits, the moving objects can be identified. Interactions between humans and animals can be hazardous. The proposed system is based on digital image processing, convolutional neural network and background subtraction method.
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