Smart cameras and vision sensors have been key tools for monitoring and controlling the manufacture and movement of products in industrial environments for many years. These devices integrate image sensors, optics and on-board processing to capture images, interpret them, and then output a result based on that interpretation. Recently, these devices have been joined by a new class of intelligent camera: inference cameras. This new class of camera uses neural networks trained with deep learning methods to classify and locate objects. This article provides an overview and comparison of these different types of cameras and how their evolution is expected to impact the design of industrial systems.
Vision sensors are typically less powerful and flexible than smart cameras. They are configured for use in specific applications by adjusting a limited set of parameters. These applications include barcode reading, or checking the presence and/or absence of a feature. Smart cameras are more powerful and flexible, but they require more advanced programming to solve their tasks, which are much more complex. Both vision sensors and smart cameras can often interface directly with external systems, including programmable logic controllers (PLCs) using the RS232 serial data interface. Many can also connect to PCs using an ethernet interface.