Optical flow techniques for estimation of camera motion parameters in sewer closed circuit television inspection videos

Halfawy, Mahmoud R.; Hengmeechai, Jantira

doi:10.1016/j.autcon.2013.10.016

Cited by 20 publications

(6 citation statements)

References 7 publications

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“… Sewage pipes are subject to extensive staining and background patterning that can appear as very sudden changes in color or shade, giving the appearance of a crack. Since the focus of this paper is on the computer vision analysis techniques, this following overview of data acquisition is brief, and the reader is referred to substantial review papers [ [24] is the most widespread approach to data collection for sewage pipe inspection; nevertheless the sewer infrastructure which has been imaged amounts only to a miniscule fraction of perhaps a few percent [19]. Because the most common approach is to have a forward-looking camera looking down the pipe, the CCTV method suffers from drawbacks of geometric distortion, a significant drawback in automated analysis.…”

Section: Underground Concrete Pipesmentioning

confidence: 99%

“…Because buried concrete pipes are patterned and poorly lit, robust feature extraction is an essential step and appears throughout the pipe inspection literature. Methods include edge detection [25] [22] or the Hough transform [22] for edge/line detection, image segmentation [26] and background subtraction [18] for foreground object extraction, methods of image registration [18] and optical flow [24] for the tracking and association of objects in successive video frames, particularly relevant in CCTV imaging. More advanced methods include texture-based methods, including co-occurrence [21] and histograms of oriented gradients [23], and multi-resolution or wavelet-based approaches [29] [17].…”

Section: Feature Extractionmentioning

confidence: 99%

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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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(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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Section: Underground Concrete Pipesmentioning

confidence: 99%

Section: Feature Extractionmentioning

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

View full text Add to dashboard Cite

show abstract

“…In order to overcome such difficulties, many studies have also been carried out. [34][35][36][37] To automate the image capture and crack detection, the use of unmanned inspection devices such as a robot or unmanned aerial vehicle (UAV) is increasingly investigated. [38][39][40][41][42] Specific application examples, bridges, road pavements, and various concrete structures are as follows.…”

Section: Introductionmentioning

confidence: 99%

Rapid and non-invasive surface crack detection for pressed-panel products based on online image processing

Jung

Park

2019

Structural Health Monitoring

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Crack detection during the manufacturing process of pressed-panel products is an important aspect of quality management. Traditional approaches for crack detection of those products are subjective and expensive because they are usually performed by experienced human inspectors. Therefore, the development and implementation of an automated and accurate inspection system is required for the manufacturing process. In this article, a crack detection technique based on image processing is proposed that utilizes the images of panel products captured by a regular camera system. First, the binary panel object image is extracted from various backgrounds after considering the color factor. Edge lines are then generated from a binary image using a percolation process. Finally, crack detection and localization is performed with a unique edge-line evaluation. In order to demonstrate the capability of the proposed technique, lab-scale experiments were carried out with a thin aluminum plate. In addition, a test was performed with the panel images acquired at an actual press line. Experimental results show that the proposed technique could effectively detect panel cracks at an improved rate and speed. The experimental results also demonstrate that the proposed technique could be an extension of structural health monitoring frameworks into a new manufacturing application.

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“…[14][15][16] The video created with a front-facing camera in a sewer inspection system can be analyzed through optical flow vectors to recover information about travelling distance, position inside the sewer, and direction of motion. 17 The method proposed is founded in an optical flow. Nevertheless, as far as we know, the method proposed in this paper is completely new.…”

Section: Introductionmentioning

confidence: 99%

Heuristic method based on voting for extrinsic orientation through image epipolarization

Martín

Lerma

Uzkeda

2017

J. Electron. Imaging

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Traditionally, the stereo-pair rectification, also known as epipolarization problem, (i.e., the projection of both images onto a common image plane) is solved once both intrinsic (interior) and extrinsic (exterior) orientation parameters are known. A heuristic method is proposed to solve both the extrinsic orientation problem and the epipolarization problem in just one single step. The algorithm uses the main property of a coplanar stereopair as fitness criteria: null vertical parallax between corresponding points to achieve the best stereopair. Using an iterative approach, each pair of corresponding points will vote for a rotation axis that may reduce vertical parallax. The votes will be weighted, the rotation applied, and an iteration will be carried out, until the vertical parallax residual error is below a threshold. The algorithm performance and accuracy are checked using both simulated and real case examples. In addition, its results are compared with those obtained using a traditional nonlinear least-squares adjustment based on the coplanarity condition. The heuristic methodology is robust, fast, and yields optimal results.

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Optical flow techniques for estimation of camera motion parameters in sewer closed circuit television inspection videos

Cited by 20 publications

References 7 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

Rapid and non-invasive surface crack detection for pressed-panel products based on online image processing

Heuristic method based on voting for extrinsic orientation through image epipolarization

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