Alrad - NEWSIGHT IMAGING range of CMOS Line and Area image sensors now available

19 Feb 2020

Newsight Imaging develops affordable CMOS image sensor-based chips, which can be customized for high volume markets in the following application areas: Automotive visual safety solutions, Autonomous home appliance robots providing sharp and clear images that accurately map the indoor environment, Drones using laser LiDAR, Bar Code Scanners, AR/VR, Automation and Industry

4.0. Here are some examples of the sensors:

The NSI1000 imager is designed for applications such as Robotics LiDAR and AR/VR,. The sensor is composed of 32 rows x 1024 pixels, and another 4 rows x 1024 pixels which are analog binned to form an ultra-high sensitive matrix. The NSI1000 supports programmable frame rates; Multiline Triangulation; Automatic exposure control to avoid saturation from close objects and enhanced sensitivity for distant objects; Automatic peak detection for Triangulation and per-frame configuration allows on-the-fly reactions to events.

The NSG3500 is a self contained line sensor which resets itself, configures itself and starts sending vision processed data out using a variety of interfaces. The internal low power processor (Cortex M4) can be programmed using standard development kits and can manage systems using GPIO ports.   The Arm® Cortex®-M4 with FPU processor supports a set of DSP instructions which allow complex algorithm execution within its embedded Arm® core and is compatible with all Arm® tools and software.

The NSI3000 CMOS Image Sensor Chip is designed for Machine Vision applications. It is composed of 8 rows of 2048 pixels each, of which 4 rows are of 4µm x 8µm pixels and 4 rows are of 4µm x 4µm pixels. Binning the large pixels provides Ultra-high sensitivity while using the small pixels provide a fine signal with an effective resolution of 8192 pixels. The NSI3000 supports programmable high frame rate speeds, allowing better analysis and reaction to events.

Full information can be found at the following link: https://