Vehicle Underbody Grommets Detection Using Computer Vision and Co-ordinate System Mercedes Benz R&D India Pvt. Limited

Format:

Book

Conference/Event

Author/Creator:

Dhumal, Abhishek Trimbak, author.

Contributor:

Prakash Kumar

Mishra, Jagdish

Nurukurthi, Lakshmi

Tote, Anuj

Conference Name:

11th SAEINDIA International Mobility Conference (SIIMC 2024) (2024-12-11 : New Delhi, India)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2024

Summary:

Manual installation of vehicle underbody Grommets is tedious task which sometimes results in incomplete and 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 and doing rework activity. Existing deep learning and 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 and Grommet between reference and test image. This approach results in precise comparison and identification of error in terms of missing or misplacing of Grommets which also offers significant saving in manual installation and rework efforts

Notes:

Vendor supplied data

Publisher Number:

2024-28-0190

Access Restriction:

Restricted for use by site license