For further information, visit: www.mipi-modules.com<\/a><\/p>\n\n\n\n Image: <\/em><\/strong>The new VC Power SoC is an FPGA accelerator for onboard image pre-processing, that is firmly integrated into the design of the VC MIPI\u00ae Camera Modules. It is available as an option for all VC MIPI\u00ae Cameras.<\/p>\n\n\n\n All VC MIPI\u00ae Cameras<\/a> are now available with a VC Power SoC integrated into the design of the tiny modules, which enables image pre-processing directly on the MIPI module. VC is thus continuing its successful series of VC Power SoM FPGA accelerators: until now, the VC Power SoM could be integrated directly in the MIPI data stream as a component in the design of a base board or on an adapter board. With the VC Power SoC, this functionality is now a direct component of the camera module. The tiny form factor of the cameras remains unchanged: the FPGA accelerator is simply attached to the back of the camera module. Compared to the original VC Power SoM, the SoC version has fewer logic cells, but offers sufficient performance for many applications with the smallest possible space and cost consumption. VC is also expanding its range of FPGA accelerators with the even more cost-effective VC Power SoM light.<\/p>\n\n\n\n Another new feature is a micro-coax option as an alternative to the VC MIPI\u00ae FPC cables, which allows the VC MIPI\u00ae Cameras to be integrated flexibly and with a cable length of up to 75 cm. FPC cables are limited to a length of around 20 cm. The specially shielded VC Coax cable<\/a> uses an I-PEX connector. For the processor side, VC has developed an ultra-compact adapter, with which the cable can be connected via the integrated MIPI CSI-2 interface to common processor boards. For even longer cable connections of up to 10 meters, the VC MIPI\u00ae Cameras are also available with an GMSL2 option.<\/p>\n\n\n\n In an AI demo, Vision Components shows the full support of all its VC MIPI\u00ae Camera Modules with the new Raspberry Pi 5 including Hailo TPU Hat at the booth. A YOLOV7 model is used, which can recognize and distinguish over 100 object classes out-of-the-box. This enables production-ready, AI-based object recognition with highly optimized computing power and at the lowest entry-level price.<\/p>\n\n\n\n <\/p>\n\n\n\n Vision Components at embedded world<\/a> For further information, visit: www.mipi-modules.com<\/a><\/p>\n\n\n\n Media Relations Vision Components<\/p>\n Do you have a media inquiry for Vision Components, require image material or would like to be added to the VC press distribution list? Contact us at press@vision-components.com<\/a>. We will contact you as soon as possible.<\/p>\n<\/div>\n\n\n\n
Vision Components at embedded world<\/a>
Nuremberg, March 11-13, 2025
Meat the VC team: Hall 2, booth 2-551<\/strong><\/p>\n\n\n\n![\"FPGA](\"https:\/\/dev.vision-components.com\/wp-content\/uploads\/2025\/02\/VC-MIPI-Power-SoC_01_small.png\")
<\/figure>\n\n\n\nVC Power SoC complements FPGA accelerators<\/h2>\n\n\n\n
Micro-coax for cable lengths of up to 75 cm<\/h2>\n\n\n\n
Full support for RPi 5 with Hailo TPU Hat<\/h2>\n\n\n\n
Nuremberg, March 11-13, 2025
Meat the VC team: Hall 2, booth 2-551<\/strong><\/strong><\/strong><\/p>\n\n\n\n