Abstract:
Textile Industrial Automation aims to take a step towards the better industrial state by targeting
the industries with little or no know how of automation and guiding them towards the better
output of their stock in the world.
With the development in the industrial world, various processes have been automated to make the
life of the people more comfortable and this automation is used by the industries now a days
frequently. Currently in Pakistan, no such automated processes are available in our industries to
provide quick solutions to the industrial problems to fix the declining economic growth of
industries in Pakistan as we still rely on the manually operated working in our industries.
Traditionally quality inspection in industry takes place via workers which is inefficient and time
taking. In this project, we want to automate the quality inspection using industrial cameras and
image processing algorithms.
We used Faster R-CNN in this project for detection of faults in fabric wit VGG16 architecture.
Training consists of around 3600 images and 7 faults are trained with around 95 percent accuracy
