The USB 3 uEye CP cameras from IDS are now available with the PYTHON 500, PYTHON 2000 and PYTHON 5000 CMOS sensors from ON Semiconductor.
The UI-3130CP model with the PYTHON 500 sensor provides more than 560 fps in full resolution (0.5 MP, 800 x 600 pixels). It is especially suitable for slow motion filming or high speed tracking applications. The UI-3140CP with the PYTHON 1300 sensor features and a low noise and a dynamic range of 57.5 dB to ensure high-contrast images for machine vision applications. Providing a resolution of 1920 x 1200 pixels (2.3 MP), the UI-3160CP with the PYTHON 2000 sensor is designed for use with full HD (>180 fps), which meets the need of both classical industrial applications and visualization tasks. If required a change to the 4:3 format (1600 x 1200 pixels), which is common in the field of medical technology, is easily possible. In the field of 1-inch -sized sensors, the UI-3180CP with the PYTHON 5000 features 5.3 MP (2592 x 2048 pixels, 68 fps, with both square 2K x 2K format and full HD available. The combination of size and number of pixels makes it suitable for use in the field of microscopy, especially eye inspection applications that benefit from switching between AOI and full resolution.
>>For more information on this product, click here
IDS Imaging Development Systems Inc.
https://en.ids-imaging.com/
781.787.0048
Traditional HMI/SCADAs are being reinvented with today's growing dependence on mobile technology. Discover how AVEVA is implementing this software into your everyday devices to...
Software-as-a-service (SaaS) gives you the technical and financial ability to respond to the changing market and provides efficient control across your entire enterprise—not just...
What happens when you adopt modern HMI solutions? Learn more about the future of operations control with these six modern HMI must-haves to help you turbocharge operator efficiency...
AVEVA System Platform (formerly Wonderware) delivers a responsive, modern operations visualization framework designed to enhance performance across all devices with context-aware...
