Embedded vision systems are used in many fields, such as industrial automation , drones, traffic monitoring, mobile devices, and automobiles. They improve production efficiency by replacing traditional manual labor with their powerful processing capabilities and diverse functions. However, with technological advancements and increasing business demands, embedded vision systems also face greater challenges, such as power consumption, complex algorithms, processor performance, and higher image resolution. What is needed are more intelligent systems, and embedded vision systems are a crucial component in realizing these intelligent systems.
Figure 1: Composition of an embedded vision system
CMOS and CCD are currently the two leading technologies used in image acquisition. CCD offers higher image quality, but over the past decade, the gap between CMOS and CCD has narrowed considerably, with CMOS showing a strong trend towards surpassing CCD in terms of power consumption and cost. Furthermore, many applications require efficient parallel processing systems, necessitating dedicated hardware processors such as GPUs, DSPs, FPGAs, and multi-core SoCs. However, this undoubtedly increases system cost, power consumption, and PCB size. Therefore, a cost-effective processor is also essential in the industry. Of course, in practical applications, we must select a suitable processor based on the system's real-time performance, power consumption, image accuracy, and algorithm complexity.
To assist users in building their own embedded vision platforms and products, Xilinx Alliance Partner Avnet has launched a series of vision application solutions, such as the PicoZed Embedded Vision Development Kit. The PicoZedSoM integrates the Xilinx Zynq-7030 All Progammable SoC, and also includes the PicoZed Expansion Board V2.0, the HDMI FMC Expansion Board (with an integrated camera interface), and a Python-1300-CSXGA (1280x1024) camera module.
Figure 2: PicoZed Embedded Vision Development Kit from Avnet
This PicoZed vision development kit is ideal for developing machine vision applications. In addition to hardware, software tools, and a wealth of licensed IP resources, it also supports the reVISIONStack technology stack. reVISIONStack includes abundant design resources such as algorithms, hardware-accelerated OpenCV libraries, and currently popular neural network training datasets. Embedded vision systems are constantly evolving, and with the efforts of major manufacturers and engineers, various bottlenecks will be overcome, leading to wider applications in machine vision, artificial intelligence, the Internet of Things, and industrial automation.
