Supports long cables! Equipped with 20 digital I/O lines with rich functionality.
The "Coaxlink Quad CXP-12" is a 4-channel CoaXPress CXP-12 frame grabber equipped with a variety of camera control functions. It can capture images from high-resolution cameras. The bandwidth from the camera to the host PC memory is 50 Gbit/s. Additionally, it can use standard coaxial cables. It provides extremely high reliability and flexibility even in harsh environments. 【Features】 ■ 4 CoaXPress CXP-12 connections: Camera bandwidth of 5,000 MB/s ■ PCIe 3.0 (Gen3) x8 bus: Bus bandwidth of 6,700 MB/s ■ 20 rich digital I/O lines ■ A variety of camera control functions ■ Memento Event Logging Tool *For more details, please refer to the PDF document or feel free to contact us.
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【Supports long cables】 ■40 meters, CXP-12 speed (12.5 Gbps) ■72 meters, CXP-6 speed (6.25 Gbps) ■100 meters, CXP-3 speed (3 Gbps) *For more details, please refer to the PDF document or feel free to contact us.
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For more details, please refer to the PDF document or feel free to contact us.
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Euresys is a leading company in the manufacturing of image, acquisition COTS boards, and image processing software. Euresys Japan Co., Ltd. serves as a base for sales and support in Japan, providing high-quality solutions and support to OEMs and system integrators around the world. As an innovative high-tech leader, Euresys designs and provides image and video acquisition components, frame grabbers, FPGA IP cores, and image processing software. Euresys operates in computer vision, machine vision, factory automation, and medical imaging. Euresys's capabilities are further enhanced by the expertise in imaging fields such as GigE Vision, USB3 Vision, CoaXPress, Camera Link, and GenICam, which has been cultivated over 30 years by the recently acquired Sensor to Image. In terms of image analysis, Euresys offers blob detection, subpixel measurement, pattern matching, color analysis, optical character recognition, barcode reading and verification, and 3D verification and classification using deep learning.