Opto-Electronics


Image sensor evaluation kits

1 December 2019 Opto-Electronics

Ams has released the NanoVision and NanoBerry evaluation kits, which provide a ready-made platform for the development of innovative solutions based on the ams NanEyeC miniature image sensor.

The NanEyeC camera is a full-featured image sensor supplied as a tiny 1 x 1 mm surface-mount module. This small form factor can produce 100 kpixel resolution up to 58 frames/s. This means it can be used for video applications in which the camera must be invisible to the end user, or be accommodated in an extremely small space – for instance, eye tracking in virtual reality headsets. It can also be applied in user presence detection, to support automatic power on/off controls in home and building automation (HABA) applications such as air conditioning, home robotics, appliances and smart lighting.

The new NanoVision demo kit is based on an Arduino development platform. It includes all necessary drivers to interface the sensor’s single-ended interface mode (SEIM) output to an Arm Cortex-M7 microcontroller. It also supports image processing including functions like colour reconstruction and white-point balancing. Using the NanoVision support package, engineers can accelerate the development of low frame-rate applications like presence detection within the familiar Arduino hardware development environment.

The NanoBerry evaluation kit uses a NanEyeC image sensor add-on board to the Raspberry Pi port and includes firmware to interface to the Raspberry Pi host processor. Engineers using the NanoBerry board can take advantage of the high-performance Arm Cortex-A53-based processor to perform more demanding operations such as object detection, object tracking and computer vision functions provided by the OpenCV library.

The NanoBerry kit is a well-equipped platform suitable for high frame-rate and low-latency applications such as eye tracking. Integration into the NanEye PC viewer enables full evaluation of the NanEyeC with access to all registers and raw image data.


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