LINE SNAPPING ALGORITHM. Investigator: Carl Haas. Line snapping is an
example of imaging assisted automation of infrastructure maintenance.
LINE SNAPPING ALGORITHM Investigator: Carl Haas Line snapping is an example of imaging assisted automation of infrastructure maintenance. It was originally developed for accurately mapping and representing pavement cracks to be sealed in the UT Automated Road Maintenance Machine (ARMM). In the ARMM operation, the system operator first traces cracks on the computer screen. Next, polylines are drawn over the pavement image for each crack as it is traced. Coordinates of the polylines are then stored in an array for subsequent processing. However, the polylines vary from the actual crack locations because of imperfect operator hand-eye coordination. This variance can be great enough to result in unsealed cracks.
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graphically visualize the modeled crack network by moving each line segment to the middle of the best box, adding a new node point at the middle of the snapped line segment, and aligning end nodes of each adjusted segment to their midpoint.
M a n u a lM a p p ing
The approach of the line snapping algorithm is to improve the alignment of the polylines with the actual cracks to be sealed by moving a small rectangular grey level averaging box along the normal between two node points (a connected line segment). The search range of the box is variable. The current search range of the bounding ± 3.5 centimeters from the position of each polyline segment. Preliminary study indicated that the search range was efficient and adequate in practice. The algorithm finds the crack location by comparing the average gray level value at each box position. It moves the polyline segment to the middle of the box that was found to be the darkest (lowest average pixel value), since the cracks are typically darker than the surrounding pavement. This logic can be reversed. The averaging function is used to compensate for typically noisy pavement images. Once the algorithm is executed, updated renderings of the polylines are made to allow the operator to verify they are aligned with the cracks that need to be sealed. The algorithm is divided into the following five major steps: 1. 2. 3. 4.
create n bounding boxes along the normal of each line segment, get the gray level values for all pixels that each bounding box contains, find the box with the lowest average pixel value, create an array which is called snap_out[] to store the results of the line snapping, and
LineSnapping
Experimental results indicated that the algorithm is executed in a fraction of a second per image, on average. At this speed, the quality and productivity benefits are worth the time spent. Finally, it is expected that the algorithm should be applicable to crack mapping on other infrastructure elements such as buildings, bridges, tunnels, and utility pipes. This research was supported by the Federal Highway Association and the Texas Department of Transportation.
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THE UNIVERSITY OF TEXAS AT AUSTIN FIELD SYSTEMS AND CONSTRUCTION AUTOMATION GROUP The Field Systems and Construction Automation Group at the University of Texas focuses on the development of automation technology for challenging field environments, driven by the need for improvements in safety, productivity, quality and environmental impact. Technology transfer to industry is a key priority. Inquiries concerning application of these statements should be directed to Dr. Carl Haas, Field Systems and Construction Automation Laboratory, Department of Civil Engineering, University of Texas, ECJ 5.200, Austin, Texas 78712-1076, (512) 471-4601, internet:
[email protected], web page: www.ce.utexas/prof/haas/home.html.
References Haas, C., “Evolution of an Automated Crack Sealer: A study in Construction Technology Development,” Automation in Construction 4, Elsevier, 293-305, 1995. Haas, C., Kim, Y. S., and Greer, R., “A Model for Imaging Assisted Automation of Infrastructure Maintenance,” Proceedings of the 2nd International Conference on Imaging Technologies: Techniques and Applications in Civil Engineering, Davos, Switzerland, May 25-30, 1997. Kim, Y. S., Husbands, J. K., Haas C., Greer, R., and Reagan, A., “Productivity Model for Performance Evaluation of the UT Automated Road Maintenance Machine,” Proceedings of the 14th International Symposium on Automation and Robotics in Construction, Pittsburgh, PA., June 8-11, 1997. Greer, R., Kim, Y. S., and Haas, C., “Teleoperation for Construction Equipment,” Proceedings of ASCE Construction Congress V, Minneapolis, MN,. October 1997.
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Kim, Y. S., “Man-Machine Balanced Control for Automation of Infrastructure Crack Sealing,” Dissertation, Department of Civil Engineering, The University of Texas at Austin, Austin, TX., December 1997. Kim, Y., Haas, C., and Greer, R., "Path Planning for a Machine Vision Assisted, Tele-operated Pavement Crack Sealer," ASCE Journal of Transportation Engineering, vol. 124, no. 2,.pp. 137-143, Mar/Apr., 1998. Kim, Y.S., and Haas, C., "A Model for Automation of Infrastructure Maintenance using Representational Forms," tentatively accepted in January 1999 to Automation in Construction.
