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GigE Vision Frame Grabbers & Image Processing

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.

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Gidel PCIe GigE Vision Frame Grabbers displayed against a digital network connectivity background

High-Performance PCIe GigE Vision Frame Grabbers: Overview & Comparison

Features & Bandwidth
Product Name HawkEye-20GigE Proc10A-40GigE Proc1C10M-120GigE Proc1C10N-120GigE (For AI)
Product Image Gidel HawkEye-20GigE: Dual 10 GigE Vision Frame Grabber displayed against a digital network connectivity background Gidel Proc10A-40GigE: Quad 10 GigE Vision Frame Grabber displayed against a digital network connectivity background Gidel Proc1C10M: 12 x 10 GigE Vision Frame Grabber displayed against a digital network connectivity background GIdel Proc1C10N: 12 x 10 GigE Vision Frame Grabber with AI option and tensor blocks displayed against a digital network connectivity background
Camera Input
Options
  • 2 × 10 GigE cameras
  • 4 × 5 GigE cameras
  • 8 × 2.5 GigE cameras
  • 20 × 1 GigE cameras
  • 4 × 10 GigE cameras
  • 8 × 5 GigE cameras
  • 16 × 2.5 GigE cameras
  • 30 × 1 GigE cameras
  • Up to 12 × 10 GigE cameras
  • Up to 4 × 100 GigE cameras
  • Up to 12 × 10 GigE cameras
  • Up to 4 × 100 GigE cameras
Camera Input
Connectors
  • 2 x SFP+, fiber optic
  • 2 x RJ45, copper
  • 1 x QSFP, fiber optic
  • 4 x RJ45, copper
  • 4 x QSFP, fiber optic
  • 12 x SFP+, fiber optic
  • 12 x RJ45, copper
  • 4 x QSFP, fiber optic
  • 12 x SFP+, fiber optic
  • 12 x RJ45, copper
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 ✓ ✓ ✓ ✓
Real-Time Encoders
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
  • HDR correction
  • Detection
  • Modular Algorithms:
    Gidel | User
  • HDR correction
  • Detection
  • Modular Algorithms:
    Gidel | User
  • HDR correction
  • Detection
  • Modular Algorithms:
    Gidel | User
  • HDR correction
  • Detection
  • Modular Algorithms:
    Gidel | User
Cooling Options
  • Active
  • Passive
  • Active
  • Passive
  • Active
  • Passive
  • Active
  • Passive

FPGA-Based GigE Vision Acquisition and Inline Processing

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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    High-Performance GigE Vision Frame Grabber Cards

    FPGA-based GigE Vision frame grabber cards for high-bandwidth acquisition and optional real-time image processing.

    Inline FPGA Image Processing Options

    Enhance Gidel PCIe GigE Vision frame grabbers with FPGA processing options for real-time image enhancement, Detection, Compression, HDR, and data optimization before host-side processing.

    Edge AI Systems with Built-In GigE Vision Frame Grabbers

    Discover Compact FantoVision systems combining NVIDIA Jetson with built-in FPGA GigE Vision frame grabbers and inline image processing options.

    System block diagram

    System block diagram

    System block diagram

    Alternative Frame Grabbers & Camera Simulator Solutions

    Explore Gidel FPGA-based frame grabber platforms for CXP-12 and Camera Link acquisition, along with Camera Simulators for system testing and validation.

    Need Help Choosing?

    Our experts can help you find the right product for your specific requirements.

    • Free product consultation
    • Technical specifications review
    • Custom configuration options
    • Volume pricing available

    Or contact us directly:

    [email protected]




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