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Carrot volume evaluation using imaging algorithms

机译:使用成像算法评估胡萝卜量

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摘要

Volume represents an important parameter in the evaluation of fruit growth and quality, and can be used as a ripeness index to forecast optimum harvest time. The first prototype towards a fruit volume detector on trees was developed by rotating a charge coupled device (CCD) camera around the produce. The prototype helped to implement new algorithms for predicting the volume of non-regular shaped fruits easier than by conventional methods. It was tested with carrots, due to their non-circular shape and a 0.98 regression coefficient between real and predicted volume was achieved with two different algorithms.
机译:体积是评估水果生长和品质的重要参数,可以用作预测最佳收获时间的成熟度指标。通过在产品周围旋转电荷耦合器件(CCD)摄像机,开发了第一个针对树木上的水果体积检测器的原型。与传统方法相比,该原型有助于实施新算法来更容易地预测不规则形状的水果的数量。由于它们是非圆形的,因此用胡萝卜进行了测试,并使用两种不同的算法获得了实际体积和预测体积之间的0.98回归系数。

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