Cameras and other equipment used in surveillance and machine vision perform a variety of different tasks, such as Image Signal Processing (ISP), video transport, format conversion, compression, and analytics.
Machine Vision (MV) uses a combination of high-speed cameras and computers to perform complex inspection tasks in addition to digital image acquisition and analysis. You can use the resulting data for pattern recognition, object sorting, robotic arm control, and more. FPGAs are ideal for MV cameras, allowing designs to accommodate a wide variety of image sensors as well as MV-specific interfaces. SoC's are ideal for smart cameras, which enable image processing inside the camera eliminating the need for PCs to run the vision processing algorithms, saving space, power, and reducing maintenance costs.
Government, municipalities, financial institutions, and businesses are driving new uses for video surveillance technologies beyond crime prevention or security into applications such as asset management, risk mitigation, retail analytics, and safety.
The challenge for camera manufacturers, however, is developing “smarter” cameras at lower price points. More and more, digital high-definition (HD) Internet protocol surveillance cameras are replacing analog cameras because of lower installation costs, scalability, and the ability to add intelligence.
Wide dynamic range (WDR) CMOS image sensor technology, for example, provides high-quality images with better resolution and higher performance under very harsh lighting conditions. Figure 1 illustrates how an Intel® FPGA is the central interface for WDR CMOS sensors.
Advanced video analytics is replacing simple motion detection to provide reliable, automated video analysis enabling operational cost savings while also providing valuable insight into customer experience and behavior. Learn how Intel® FPGAs can be used for advanced video analytics.