Computer Vision (CV) is a branch of Artificial Intelligence that aims to enable machines to simulate the human visual system by extracting features of the physical world from images and videos usually taken by a camera. It includes several tasks with different goals: image classification, image segmentation, object detection, etc. To perform them, CV today’s applications exploit the most diverse algorithms and tools involving geometric transformations, filtering operations, and also modern Deep Learning technologies such as Convolutional Neural Networks. This work explores the possibility of using them as a proof of concept for an automatic a posteriori check on the assembly of automotive seat frame parts, specifically colored motors, in an industrial environment where a bench lets the frames translate back and forth while a camera captures the scene from above.