Vehicle Underbody Grommets Detection Using Computer Vision and Co-ordinate System

Manual installation of vehicle underbody Grommets is tedious task which sometimes results in incomplete & inaccurate installation. Based on process quality guidelines, this comes under potential defect category at End of line inspection area for which few hours of manual efforts are required for identifying location of error & doing rework activity. Existing deep learning & image comparison method falls short in identifying error location. To overcome this challenge, deep learning algorithm with co-ordinate system developed which comprises of identifying class or category of entities present in test and reference image and indexing it as Grommet or Hole. This further comprises of determining 2D position in terms of X and Y co-ordinate of each indexed hole & Grommet between reference & test image. This approach results in precise comparison & identification of error in terms of missing or misplacing of Grommets which also offers significant saving in manual installation and rework efforts.