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

机译:一种自适应地确定图像中参考圆圈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:旨在解决的准确水下定位检测探针的问题的基础上,可有效地解决这一问题的计算机视觉本文提出的方法。这种方法的原理是:第一,由于热管的形状信息是类似于图像中的圆圈,我们可以发现其物理位置的图像中是公知的圆,我们设置这个圆作为基准圆。第二,我们计算该像素的参考圆和在图片中的探针之间的偏移,并调整通过所述偏移转向齿轮。其结果是,我们可以精确地测量所述探针和所述被测热管之间的物理距离,那么我们可以知道探针水下的精确位置。然而,如何选择图像参考圆是一个棘手的问题。在本文中,我们提出了一种算法,可以自适应确定基准圆的面积。在这个区域,只会有一个圆圈,圆圈是参考圆。测试结果表明,提取在整个画面的基准圆,而无需使用所述参考圆的ROI(关心区域)的算法的准确度仅是58.76%,并且,该算法是95.88%。实验结果表明,所提出的算法能有效地提高管检测的效率。

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