A modular and scalable architecture for PC-based real-time vision systems

PC-based real-time vision systems are becoming a de facto standard in industrial applications. They are composed of an illumination system, an image acquisition system and a processing system. In this article, a modular and scalable architecture for real-time vision systems is proposed. On the one hand, we define an acquisition module that allows simultaneous acquisition of up to three monochrome cameras. The acquisition system can be scaled by adding more acquisition modules. The architecture allows simultaneous acquisition of all the modules. On the other hand, we define a processing system composed of different modules and sub-modules which specialize in a particular task: the master module interacts with the external systems; the slave module interacts with the acquisition system and manages the results of its processing sub-modules; each processing sub-module processes the information provided by one single camera. Scalability is provided by increasing the number of slave modules and processing sub-modules that compose the complete vision system. Fast real-time applications can be achieved by assigning one processor per processing sub-module. In this case, multiple PC can be used. Inter-computer communication among modules is carried out by means of sockets (following a master-slave design pattern); intra-computer communication is carried out by means of pipes, shared memory and events. We emphasize herein some real-time considerations related to the multi-processor architecture and the multitasking operating system that allow the implementation of the proposed architecture for real-time vision systems applications. An implementation of this architecture is exemplified with an application successfully installed in a manufacturing company. (C) 2003 Elsevier Science Ltd. All rights reserved.