8 March 2018 A localization algorithm of adaptively determining the ROI of the reference circle in image
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Proceedings Volume 10611, MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 1061110 (2018) https://doi.org/10.1117/12.2283126
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China
Abstract
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.
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Zeen Xu, Zeen Xu, Jun Zhang, Jun Zhang, Daimeng Zhang, Daimeng Zhang, Xiaomao Liu, Xiaomao Liu, Jinwen Tian, Jinwen Tian, } "A localization algorithm of adaptively determining the ROI of the reference circle in image", Proc. SPIE 10611, MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 1061110 (8 March 2018); doi: 10.1117/12.2283126; https://doi.org/10.1117/12.2283126
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