Industrial vision in deep learning for the food industry
Deep capture allows the identification and detection of several defects classes in real time at a rate of approximately 5000 parts / hour. The deep learning machine vision system is integrated on a conveyor at the output of an overhead cutting and winding system.
Example of the faults classes detected:
- Hematomas and haemorrhages
- Presence of the whip
- Feathers
- Broken bones
- Badly rolled up wings
The subject complexity lies in the products shapes and appearance variability as well as certain defects are subject to interpretation.
