High-speed embedded camera modules with ultra-short exposure times

Inelco Hunter has announced the availability of the TechNexion range of Embedded Camera Modules. TechNexion are manufacturers of a wide range of Embedded Vision and Embedded SoM products. The embedded camera modules are high-performance, industrial-grade solutions to accelerate time-to-market. The fast-moving AI market will be a major application for the camera modules.

The embedded vision camera modules incorporate Global Shutter or Rolling Shutter Sensors up to 13MP, capturing high-speed dynamic targets clearly with ultra-short exposure times even in low-light conditions. A C-Mount or S-Mount is provided for interchangeable lenses, making the modules very flexible and quick to configure. All cameras are natively compatible with Technexion System-on-Modules and work out of the box.

The TechNexion System-on-Modules are built around the NXP i.MX6 / i.MX7 / i.MX8M families, providing high-performance, industrial-grade building blocks to integrate into the end-product. TechNexion is an NXP Gold Partner and utilises NXP 32-bit and 64-bit ARM™ i.MX processors.

They are powerful multimedia and Edge computing platforms that include the latest connectivity options such as USB 3.0, PCI-Express, Gigabit Ethernet, Wi-Fi, Bluetooth, Full HD video encoding and decoding, plus high-performance 3D graphics. Built-in NPU with 2.3 TOPS computation power make it the perfect solution for edge computing like real time machine vision applications.

If the ultimate in power is needed for AI or Machine vision, Technexion offers Embedded Systems based on the Nvidia Jetson NX/Orin Nano microprocessor, which provides 21 TOPS/40 TOPS computation power and can support up to 24 cameras with synchronous video capture and analytics.

For compact and cost-effective robotic solutions, Technexion’s ROVY System-on-Modules are just a little bigger than a playing card, with MPU, MCU, DSP, GPU and MMA support. The performance is up to 8 TOPS computation power, making them well-suited to robotic and machine vision applications.


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