Deep-learning based industrial quality control on low-cost smart cameras

Abstract

This paper aims to describe a combined machine vision and deep learning method for quality control in an industrial environment. The innovative approach used for the proposed solution leverages the use of low-cost hardware of reduced size, and yields extremely high evaluation accuracy and limited computational time. As a result, the developed system works entirely on a portable smart camera. It does not require additional sensors, such as photocells, nor is it based on external computation.