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A localization algorithm of adaptively determining the ROI of the reference circle in image

机译：一种自适应确定图像中参考圆的ROI的定位算法

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Aiming at solving the problem of accurately positioning the detection probes underwater, this paper proposed a method based on computer vision which can effectively solve this problem. The theory of this method is that: First, because the shape information of the heat tube is similar to a circle in the image, we can find a circle which physical location is well known in the image, we set this circle as the reference circle. Second, we calculate the pixel offset between the reference circle and the probes in the picture, and adjust the steering gear through the offset. As a result, we can accurately measure the physical distance between the probes and the under test heat tubes, then we can know the precise location of the probes underwater. However, how to choose reference circle in image is a difficult problem. In this paper, we propose an algorithm that can adaptively confirm the area of reference circle. In this area, there will be only one circle, and the circle is the reference circle. The test results show that the accuracy of the algorithm of extracting the reference circle in the whole picture without using ROI (region of interest) of the reference circle is only 58.76% and the proposed algorithm is 95.88%. The experimental results indicate that the proposed algorithm can effectively improve the efficiency of the tubes detection.
机译：为了解决检测探针在水下的精确定位问题，提出了一种基于计算机视觉的方法，可以有效地解决这一问题。这种方法的原理是：首先，由于热管的形状信息类似于图像中的圆，因此我们可以找到一个物理位置在图像中众所周知的圆，我们将此圆设置为参考圆。其次，我们计算参考圆和图片中探针之间的像素偏移，并通过该偏移调整转向器。结果，我们可以准确地测量探头与被测热管之间的物理距离，然后我们可以知道探头在水下的精确位置。然而，如何在图像中选择参考圆是一个难题。在本文中，我们提出了一种可以自适应确定参考圆的面积的算法。在此区域中，将只有一个圆，该圆是参考圆。测试结果表明，在不使用参考圆的ROI（感兴趣区域）的情况下，在整个图片中提取参考圆的算法的准确度仅为58.76％，所提算法为95.88％。实验结果表明，该算法可以有效提高检测管的效率。

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