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A Simple and Efficient Algorithm Design for Improving the Infrared Tracking Accuracy of Smart Cars

机译:一种简便高效的算法设计,用于提高智能汽车红外跟踪精度

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The smart car collects the signal through the infrared sensor, and obtains the gray map in front of the car, according to the gray map, the tracking is judged.Due to the complexity of the environment, many gray-scale maps are difficult to trace, and even cannot be judged, which brings great uncertainty to the operation of the smart car.The paper designs a method to improve the infrared tracking accuracy of smart cars.First, determine the level of contrast in this graph.By improving the brightness in the grayscale image, the gray signal around the tracking line is eliminated, and then the tracking line is highlighted by increasing the contrast.Therefore, it effectively overcomes the shortcomings of poor practicality of smart cars and improves the infrared tracking accuracy of smart cars.
机译:智能车通过红外传感器收集信号,并根据灰色地图获取汽车前面的灰色地图,判断跟踪。为环境的复杂性,许多灰度映射难以跟踪,甚至不能判断,这给智能汽车的操作带来了很大的不确定性。本文设计了一种提高智能汽车红外跟踪精度的方法。首先,确定了该图中对比度的对比度。从而提高亮度灰度图像,跟踪线周围的灰色信号被淘汰,然后通过增加对比度突出显示跟踪线。因此,它有效地克服了智能汽车实用性差的缺点,提高了智能汽车的红外跟踪精度。

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