Author: Rossana Ballardini

Specialvideo proposes an incremental workflow to automate the quality control of finished fabrics with Artificial Intelligence.

The neural networks underlying Artificial Intelligence for computer vision must be trained with real images of the product to distinguish defective portions of finished fabrics in the continuous flow of compliant products.
It is true that AI is flexible and can give surprising results on similar products never seen before, but it is also true that the best performance is achieved by providing Artificial Intelligence with images acquired in the field of the same textile industry for which the system is intended.

Specialvideo has designed a progressive path for integrating AI into quality control for continuous textile production, which is structured in implementation and study phases:

1. Fully operational vision system with linear camera for inspecting solid colours.
2. Colour acquisition for printed fabrics and weave inspection to train neural networks.
3. Extension of colour functionality and definition of specifications for print and weave defects.
4. Updating of the first system and supply of following systems complete with Artificial Intelligence.

Therefore, the first fabric inspection system installed in the factory has two purposes:

• inspecting solid colours

Solid colour inspection implements monochromatic processing capable of finding stains, holes and other alterations.
Each product non-conformity is stored in the digital defect map, the file that represents the reel by tracking the defective portions of the fabric and their position on the roll.

• acquiring images of prints and weaves for the purpose of training AI

The same vision system is activated by the customer in colour image acquisition mode for AI training, in order to capture the portions of fabric with defects.
During these acquisition sessions, defects must be marked in advance with adhesive labels.

The vision system is capable of recording counts and statistics useful in the context of Industry 4.0.

To learn more about Specialvideo’s experience in the field of visual inspection with linear cameras, please read the case history of vision systems for PVC rolls.

Using Ultralytics’ YOLO models, Specialvideo has developed a reliable, high-precision quality control system for pizzas that identifies, counts, and verifies toppings on the fly.