ADLINK Technology
Intel® Atom™ Quad-Core Processor E3845 1.9 GHz-based smart camera with 2MP, 120fps, global shutter sensor with 16G SSD
Mfg Part Number: NEON-1020/SSD16G , Item #: 1572725
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, PO and Wire.
High performance increases speed and capture complexity
- High end quad core processor -
Intel® Atom™ processor E3845 at 1.91GHz improves dramatically on the performance of existing smart cameras. The high end processor provides up to 6 times the computing power of conventional smart cameras.
- Improved detection sensitivity -
The 4 MP 60 fps 1-inch global shutter sensor improves on rolling shutter sensors with improved raw image clarity, for high speed inspection precision.
- Coordination among CPU, GPU and FPGA co-processor -
The NEON-1040' s FPGA accelerates image pre-processing and reduces CPU loading, making it ideal for complex acquisitions like those in LUT (look up table), ROI (region of interest), and shading correction. Thanks for FPGA, the CPU resource can focus on algorithm and make inspection tasking more efficiency.
The NEON-1040' s built-in PWM lighting control module eliminates the need for additional lighting controller equipment, reducing TCO.
- Programming in the x86 architecture -
NEON-1040 is based on x86 architecture, with all development environments familiar to users, for motion/HMI/IO solutions, seamless migration from the original x86 platform.
- Rich third party software support-
The NEON-1040 provides flexible software support for MVTec HALCON, STEMMER IMAGING Common Vision Blox, Adaptive Vision, Open CV, Open CL and more. As well, GeniCam and GenTL compatibility simplify communication with devices and allow third party software to control cameras and acquire image data.
- 64-bit computing -
As image analyses software have to deal with great bulk of data, most mainstream software products in this segment support 64-bit instructions. Therefore, it is better for implementers to choose a vision system that supports 64-bit computing environment.
Intel® Atom™ processor E3845 at 1.91GHz improves dramatically on the performance of existing smart cameras. The high end processor provides up to 6 times the computing power of conventional smart cameras.
- Improved detection sensitivity -The 4 MP 60 fps 1-inch global shutter sensor improves on rolling shutter sensors with improved raw image clarity, for high speed inspection precision.
- Coordination among CPU, GPU and FPGA co-processor -The NEON-1040' s FPGA accelerates image pre-processing and reduces CPU loading, making it ideal for complex acquisitions like those in LUT (look up table), ROI (region of interest), and shading correction. Thanks for FPGA, the CPU resource can focus on algorithm and make inspection tasking more efficiency.
Maximum integration reduces TCO
- Built-in PWM lighting control -The NEON-1040' s built-in PWM lighting control module eliminates the need for additional lighting controller equipment, reducing TCO.
Open architecture and easy development dramatically reduce time to market
In a real application environment, different development languages and software tools are required in machine vision, motion controller, smart camera and line scan camera stations . A platform allowing development in a single language, with easy deployment from existing platforms, conserving manpower costs and reducing time to market.- Programming in the x86 architecture -
NEON-1040 is based on x86 architecture, with all development environments familiar to users, for motion/HMI/IO solutions, seamless migration from the original x86 platform.
- Rich third party software support- The NEON-1040 provides flexible software support for MVTec HALCON, STEMMER IMAGING Common Vision Blox, Adaptive Vision, Open CV, Open CL and more. As well, GeniCam and GenTL compatibility simplify communication with devices and allow third party software to control cameras and acquire image data.
- 64-bit computing -As image analyses software have to deal with great bulk of data, most mainstream software products in this segment support 64-bit instructions. Therefore, it is better for implementers to choose a vision system that supports 64-bit computing environment.
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