FSM-IMX334M-00G-V1A – Monochrome Sensor with M12 Mount
Discover the FSM-IMX334M-00G-V1A featuring Sony IMX334 sensor and M12 Mount for advanced grayscale imaging.
Explore IMX334:
Product Overview
Monochrome sensor module with Sony IMX334 8.3 MP CMOS sensor and M12 Mount, ideal for high-resolution grayscale imaging applications.
The FSM-IMX334M-00G-V1A is a monochrome sensor module featuring the Sony IMX334 8.3 MP CMOS sensor, integrated into a compact 26.5 mm x 26.5 mm module with an M12 Mount (CMT168) for lens compatibility. The high-resolution sensor delivers exceptional grayscale image quality suitable for advanced imaging applications. The module supports a MIPI CSI-2 interface with up to 4 data lanes, enabling high-speed data transmission at up to 60 fps.
As part of the FRAMOS Sensor Module Ecosystem, this module facilitates flexible integration with various processing platforms through FRAMOS Sensor Adapters (FSA) and Processor Adapters (FPA). The standardized Software Pack includes reference drivers for platforms like NVIDIA® Jetson™ TX2 and Jetson™ AGX Xavier™, streamlining development.
All necessary components to start capturing images are available off the shelf, allowing immediate evaluation. FRAMOS recommends purchasing the FSM and platform-specific Development Kit (Devkit) for optimal results. Learn more about our Embedded Image Sensor Ecosystem.
Product Specifications
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![Pixel Size x [µm]](data:image/svg+xml;base64,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)
Pixel Size x [µm] - 2
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![Pixel Size y [µm]](data:image/svg+xml;base64,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)
Pixel Size y [µm] - 2
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Chromatics - Color, Monochrome
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Data Interface - MIPI CSI-2
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![Data Lanes [#]](data:image/svg+xml;base64,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)
Data Lanes [#] - 4
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![Horizontal Resolution [px]](data:image/svg+xml;base64,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)
Horizontal Resolution [px] - 3840
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Integrated Lens - No
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Lens Mount - C/CS-Mount (FMA-MNT-CCS/265-V1A), M12 Mount (CMT168), M12 Mount (CMT821B), M12 Mount (DW LH-15.0), No Lens Mount
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Manufacturer - FRAMOS
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![Max. Frame Rate [fps]](data:image/svg+xml;base64,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)
Max. Frame Rate [fps] - 60
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![Pixel Depth(s) [bit]](data:image/svg+xml;base64,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)
Pixel Depth(s) [bit] - 10, 12
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Product Type - Framos Modules
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![Resolution [MP]](data:image/svg+xml;base64,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)
Resolution [MP] - 8.3
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Sensor Manufacturer
- Sony
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Sensor Name - IMX334LLR
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Sensor Technology - CMOS
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Shutter Type - Rolling Shutter
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Welcome to our blog section, where knowledge meets inspiration. Explore insightful articles, expert tips, and the latest trends in our field.
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Inside-Out, Outside-In: Two Ways Vision AI Enters the Factory
Physical AI is moving from research labs onto the factory floor along two distinct paths. One begins with digital twins, simulation, and synthetic data before a robot reaches real hardware....
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Bridging Sensor and SoC: Co-Optimization Strategies for Next-Generation Vision
As imaging moves toward smarter, faster, and more efficient systems, modern vision applications demand more than incremental improvement. They require deeper synergy and better co-optimization between sensors and SoCs. Design...
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Unlocking New Capabilities: How Sony’s Image Sensors Are Advancing Industrial Vision
Industrial vision is evolving to support faster, more accurate, and more adaptable inspection. Advances in image sensors – from high-resolution and HDR imaging to short-wave infrared – are enabling better...
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Embedded Vision Beyond Autonomous robots
Embedded vision is widely recognized in modern mobility applications such as autonomous driving, advanced driver-assistance systems (ADAS), AMRs, AGVs, drones, and humanoid robots. Besides these relatively new application areas, there...
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From Prototype to Production: Building AI at the Edge
An AI model that works on a development board is still a long way from a production-ready edge device. The final system must capture useful data, process it within a...
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Industrial 3D Cameras: Rugged 3D Vision Camera for Automation – FRAMOS D435e with GigE & IP66
3D cameras for industrial applications have to operate in harsh production environments and reliably detect moving objects at speed, e.g. when the camera is mounted on a robot arm. Stable...
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Depth Sensing Cameras: How Machines Understand the Physical World
The past two decades of innovations in embedded systems, robotics, industrial automation and autonomous vehicles all have one thing in common.
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When Robot Safety Becomes a Perception Problem
For decades, robot safety was based on separation. Cages, light curtains, guarded workcells, and emergency stops kept machines and people apart. Physical AI changes that model. Robots increasingly share space...
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