Shape Measurement of a Sewer Pipe Using a Mobile Robot with Computer Vision

(2015) A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure. Advanced Engineering Informatics, 29 (2). pp. 196-210. ISSN 1474-0346 Access from the University of Nottingham repository: http://eprints.nottingham.ac.uk/31986/1/Manuscript_KochEtAl_2015_accepted.pdf Copyright and reuse:The Nottingham ePrints service makes this work by researchers of the University of Nottingham available open access under the following conditions. This article is made available under the Creative Commons Attribution Non-commercial No Derivatives licence and may be reused according to the conditions of the licence. For more details see: http://creativecommons.org/licenses/by-nc-nd/2.5/ A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription.For more information, please contact eprints@nottingham.ac.uk 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 Abstract:To ensure the safety and the serviceability of civil infrastructure it is essential to visually inspect and assess its physical and functional condition. This review paper presents the current state of practice of assessing the visual condition of vertical and horizontal civil infrastructure; in particular of reinforced concrete bridges, precast concrete tunnels, underground concrete pipes, and asphalt pavements. Since the rate of creation and deployment of computer vision methods for civil engineering applications has been exponentially increasing, the main part of the paper presents a comprehensive synthesis of the state of the art in computer vision based defect detection and condition assessment related to concrete and asphalt civil infrastructure. Finally, the current achievements and limitations of existing methods as well as open research challenges are outlined to assist both the civil engineering and the computer science research community in setting an agenda for future research. Keywords:Computer Vision, Infrastructure, Condition assessment, Defect detection, Infrastructure monitoring Research Highlights: Visual inspection of civil infrastructure is essential for condition assessment.  We focus on concrete bridges, tunnels, underground pipes, and asphalt pavements.  Accordingly, we review the latest computer vision based defect detection methods.  Using computer vision most relevant types of defects can be automatically detected.  Automatic defect properties retrieval and assessment has not been achieved yet . 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 ...

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“…For pipe inspection, methods for 3D reconstruction based on laser illumination are developed in Duran et al [27] [20] and Kawasue et al [89].…”

mentioning

confidence: 99%

A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure

Koch

Georgieva

Kasireddy

et al. 2015

Advanced Engineering Informatics

797

336

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“…The system can detect scratches on the high gloss metal sheet with a typical width of 1 μm and a depth of 40 nm. Kawasue and Komatsu [11] proposed a mobile robot equipped with two lasers and a CCD camera for pipeline inspection. The mobile robot can reconstruct the 3D shape of the sewage pipeline.…”

Section: Introductionmentioning

confidence: 99%

Application of machine vision technology in geometric dimension measurement of small parts

2018

J Image Video Proc.

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In this paper, the on-line detection of small parts' dimension measurement based on machine vision is designed, and the key technologies, such as image processing, image registration and stitching, edge detection, sub-pixel location analysis, image feature recognition and clustering, and scale measurement based on image involved in the detection of small part dimension are studied. Firstly, based on the actual usage and the characteristics of the algorithm, the feature-based SIFT algorithm was selected to complete the image registration, and the image edge detection algorithm and data processing method were explored. The histogram equalization improves the grayscale distribution of the stitched image and improves the contrast of the image. The median noise filtering algorithm was used to complete the image noise reduction. The false edge was filtered to get the single pixel edge, and the least square method was used to compensate the missing edge pixels and reduce the measurement error. An accurate image registration transformation matrix was obtained. Then, the weighted average fusion algorithm was used to complete the image fusion. The experimental results show that the image stitching algorithm is accurate and effective, and the measurement accuracy of the system meets the performance requirements.

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“…Furthermore, when a system of multiple robots is considered, control and coordination are complex and demanding tasks. According to [16], vision systems for mobile agents, can be classified in six types, sensing and perception [31,23,9,17,7], mapping and self-localization [22,2,4], recognition and location [5,28,29,30,14], navigation and planning [13,20], tracking [21,19,1] and visual servoing [25,11,27].…”

Section: Introductionmentioning

confidence: 99%

Vision System for the Navigation of a Mobile Robot

González

Sánchez

Díaz

et al. 2018

CyS

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In this paper the development of an object detection system in a controlled two-dimensional space using computer vision techniques is presented. The detected objects have a rigid geometry and are exposed to real light; therefore, the system is robust to changes in lighting and shading. In order to handle the large amount of data to be processed in real time, a MyRIO device which contains an FPGA is used. This device allows communication with the LabVIEW software where the user interface resides. Using LabVIEW a tracking by color algorithm is implemented, in order to attend to a reactive agent, which uses an infrared sensor to detect the distance to an obstacle and perform the functions of foraging and storage. In order to improve performance, a supervisory system was implemented using a Kinect device that provides information relative to the position of the objects in the test area. This information allows eliminating occlusion problems.

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Shape Measurement of a Sewer Pipe Using a Mobile Robot with Computer Vision

Cited by 18 publications

References 15 publications

A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure

A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure

Application of machine vision technology in geometric dimension measurement of small parts

Vision System for the Navigation of a Mobile Robot

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