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A Computer Vision Algorithm for Omnidirectional Bee Counting at Langstroth Beehive Entrances

机译:Langstroth蜂巢入口处全向蜂计数的计算机视觉算法

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A computer vision algorithm is proposed for omnidirectional bee counting in images of Langstroth beehive entrances captured hi situ with a miniature camera connected to a multi-sensor, solar-powered electronic beehive monitoring device. The algorithm consists of three stages: pre-processing, landing pad identification, and omnidirectional bee counting. In the pre-processing stage, an approximate image region where the landing pad is likely to be is cropped and the brightness of the cropped image adjusted. The landing pad identification is obtained through iterative reduction of the cropped image to the actual landing pad. Omnidirectional bee counts are computed by dividing the total number of bee pixels by the average number of pixels occupied by individual bees. The algorithm was evaluated on 1,781 images from two electronic beehive monitoring devices deployed hi Langstroth beehives with live honeybees and achieved an accuracy of over 80 per cent compared to the ground truth obtained from human evaluators.
机译:提出了一种计算机视觉算法,用于通过微型摄像机连接到多传感器,太阳能电子蜂箱监控设备在现场捕获的Langstroth蜂箱入口图像中进行全向蜂计数。该算法包括三个阶段:预处理,着陆区识别和全向蜜蜂计数。在预处理阶段,裁剪可能会着陆垫的近似图像区域,并调整裁剪图像的亮度。通过将裁剪后的图像迭代缩小为实际的着陆垫来获得着陆垫标识。通过将蜜蜂像素的总数除以单个蜜蜂所占像素的平均数量来计算全向蜜蜂计数。该算法在来自两个电子蜂箱监测设备的1,781张图像上进行了评估,该设备在带活蜜蜂的Langstroth蜂箱中部署,与从人类评估者那里获得的地面真相相比,其准确性达到80%以上。

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