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SUMMARY:Mapping grout lines in images to enable automated visual inspectio
 n of masonry arch bridges - Dan Brackenbury\, PhD Candidate\, Engineering 
 Department
DTSTART:20180302T150000Z
DTEND:20180302T160000Z
UID:TALK101584@talks.cam.ac.uk
CONTACT:Karen Mitchell
DESCRIPTION:Currently\, the condition of masonry arch bridges are predomin
 antly assessed via manual visual inspection. This process carries risk and
  cost due to the need for an inspection engineer to access sites in the pr
 oximity of busy railway lines and roads. Manual visual inspection is also 
 known to be subjective\, relying on the inspection engineer’s interpreta
 tion of the structures condition. The collection of image and laser scan d
 ata is becoming increasingly fast (and this will continue with the use of 
 drones for this purpose). There is therefore a large opportunity to collec
 t and use this data to automate the visual inspection process through digi
 tal means.\n\nHowever\, Masonry surfaces are often rough\, and the grout-l
 ine patterns create a non-homogenous surface\, making defect detection har
 der. Therefore\, as a precursor to defect detection\, a methodology has be
 en developed to filter the individual bricks out from masonry images\, ena
 bling defect detection on the more homogeneous brick surface. This uses a 
 deterministic approach\, first detecting the position of grout-lines\, and
  from these positions determining the brick spacing pattern\, to then remo
 ve false grout-lines and add undetected grout-lines. The methodology has t
 hen been tested by applying a rudimentary crack detection process on mason
 ry images with the grout lines masked. This applies a simple edge detectio
 n procedure and uses the geometry of detected points relative to one anoth
 er to filter out genuine cracks from background noise.
LOCATION: Cambridge University Engineering Department\, LT6
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