HawkEye-20GigE
Dual 10 GigE Vision Frame Grabber & Image Processing System
Smart NIC
Gidel GigE Vision Frame Grabbers and FPGA Image Processing solutions deliver high-bandwidth capture with deterministic, low-latency performance. The portfolio scales from compact dual-port 10 GigE frame grabber cards to ultra-high-throughput boards supporting acquisition from up to 12 × 10 GigE Vision cameras, providing a scalable fit for demanding imaging and vision workloads.
| Product Name | HawkEye-20GigE | Proc10A-40GigE | Proc1C10M-120GigE | Proc1C10N-120GigE (For AI) |
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| Host Interface (PCIe) | Gen3 x8 | Gen3 x8 | Gen3 x16 | Gen3 x16 |
| On-Board Memory | Up to 17GB | Up to 33GB | 8GB | 8GB |
| Real-Time ROI Offload | ✓ | ✓ | ✓ | ✓ |
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| Encoder Throughput (per camera) |
> 1 Giga pixel/s | > 1 Giga pixel/s | > 1 Giga pixel/s | > 1 Giga pixel/s |
| Real-Time FPGA Image Processing |
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Gidel PCIe GigE Vision frame grabbers manage high-bandwidth camera acquisition directly on the Altera FPGA, enabling deterministic, low-latency data capture while reducing CPU overhead. Optional inline FPGA processing supports real-time image enhancement, Compression, HDR, Detection, and data optimization before host-side processing.
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System block diagram
System block diagram
System block diagram
Reuven Weintraub, founder and CTO of Gidel, reveals how to unlock exceptional image processing performance by adding FPGA’s processing at Vision Show, Stuttgart 2024.
Gidel frame grabbers and edge AI vision at the Embedded World show 2024.
Boost your vision! Brief introduction of Gidel’s Frame Grabber range – 2023.
Gidel presented its FPGA-based architecture capable of processing Giga+ Pixels per second while maintaining exceptionally low power consumption.
The session demonstrated how Gidel’s scalable FPGA solutions deliver real-time imaging performance, energy efficiency, and deterministic throughput for advanced vision and imaging systems.
Presented by Reuven Weintraub, this talk highlighted Gidel’s expertise in real-time processing over Gigapixel/s image streams, demonstrating how FPGA-based architectures enable deterministic latency, scalable throughput, and efficient handling of ultra–high-resolution vision data.
Reuven Weintraub – Gidel’s founder and CTO presents Frame Grabber innovations at Embedded World show 2022.
The right GigE Vision frame grabber depends mainly on the number and speed of the cameras, aggregate bandwidth, on-board memory, host interface, and processing requirements. Gidel offers solutions ranging from dual and quad 10 GigE acquisition to high-throughput 12 × 10 GigE systems, including options with high-bandwidth HBM2 memory and FPGA-based AI acceleration.
Yes. Gidel’s PCIe GigE Vision frame grabbers can perform optional inline FPGA processing during acquisition, before image data reaches the host PC. Available capabilities include Compression, HDR correction, Detection, image enhancement, ROI processing, and custom FPGA algorithms.
Yes. Gidel’s InfiniVision architecture supports deterministic, synchronized acquisition from 100+ GigE cameras across scalable multi-card systems. It manages synchronization, bandwidth, connectivity, buffering, and data aggregation for demanding multi-camera imaging applications.
Gidel provides dedicated software, drivers, APIs, and GUI tools for camera configuration, image acquisition, system control, and application integration. For applications requiring customized FPGA processing, the ProcVision Suite provides development, debugging, and validation tools for integrating proprietary algorithms directly into the image acquisition pipeline.
A PCIe GigE Vision frame grabber installs in a host computer and transfers acquired image data through PCIe. A Gidel FantoVision system combines GigE Vision acquisition, an NVIDIA Jetson processor, and optional real-time FPGA image processing in a compact Edge AI computer. The correct platform depends on whether the application requires a host-based PCIe card or a complete embedded vision system.
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