Industrial Quality Control uses scientific techniques and modern methods to determine product and service capabilities, to enable an organization to economically provide a product or service suitable for its intended purpose. The objective of a good quality-control program is to enable all people and machines concerned to do their jobs right the first time and to provide assurance to the customer that this has been done.
Industrial quality control is one of the most common areas of use of machine vision cameras. Our cameras offer superior performance and image quality. On board image processing can make a difference where every millisecond counts.
Thanks to their versatility, extensibility and flexibility, OptoMotive´s cameras can be used in a wide range of applications, such as:
Did you know that…
… an FPGA-based camera can save you money as well?
Implementing new features and responding to changing market requirements by using FPGAs is easy. Because processors are implemented as soft-hardware, board redesigns are not necessary. The ability to update firmware over Ethernet or USB is a common feature in today´s FPGA systems. Upgrading such a vision system is simple and minimizes time-to-market and thus minimizes costs of application. When an application needs to be moved to high-volume production due to reducing production costs, it is easy to migrate from FPGA to ASIC in a matter of weeks and thus even further reduce production costs in a very short time.
In an FPGA-based camera all of the abovementioned very much counts as well. But the benefits of such a system in image processing also means the possibility of image processing inside the camera itself. That also results in reducing data transmission costs. Where there is a need for high-resolution and high-speed, in combination with demands for real-time reaction, FPGAs are the best solution.
Furthermore on an FPGA-based camera two major bottlenecks are avoided at the same time. There is no longer any problem with the transmission of data to the host computer, nor is there is a problem with real-time processing ability of the host PC. Several different machine vision tasks can be implemented in the FPGA of such cameras. From pixel-processing pipelines which include look-up tables, to 1D, 2D and 3D filtering, image statistics cores, such as auto-exposure, auto-gain, auto-white-balance etc., and at last, but not least, a higher level processing of data remainder with the soft CPU. This means that an FPGA-based camera can operate as autonomous device, doing everything that complex machine vision systems do. It can even do object recognition and character recognition by itself.