{"product_id":"arducam-b0184-b0188-imx219-low-distortion-camera-module-drop-in-replacement-for-raspberry-pi-v2-camera-and-jetson-nano-camera","title":"Arducam B0184 \/ B0188 IMX219 Low Distortion Camera Module-drop-in replacement for Raspberry Pi V2 Camera and Jetson Nano Camera","description":"\u003cmeta name=\"description\" content=\"Buy Arducam B0184 \/ B0188 IMX219 Low Distortion Camera Module-drop-in replacement for Raspberry Pi V2 Camera and Jetson Nano Camera online in India at best price from The Engineer Store, Bengaluru. Authentic product, 7-day warranty on manufacturing defects, fast delivery across India.\"\u003e\n\n\u003ch1\u003eArducam B0184 \/ B0188 IMX219 Low Distortion Camera Module-drop-in replacement for Raspberry Pi V2 Camera and Jetson Nano Camera\u003c\/h1\u003e\n\n\u003cp\u003eThe Arducam B0184 \/ B0188 IMX219 Low Distortion Camera Module is a high-performance 8-megapixel camera module featuring the Sony IMX219 sensor with advanced low-distortion optics, designed as a direct drop-in replacement for Raspberry Pi V2 and Jetson Nano camera interfaces. This module is widely used by computer vision engineers, roboticists, and embedded systems developers who require superior image quality with minimal barrel distortion for precision applications including object detection, autonomous navigation, and industrial inspection systems. It solves the critical problem of optical distortion inherent in standard camera modules by incorporating specialized lens correction algorithms and premium optical components, enabling accurate pixel-level analysis essential for machine learning and real-time image processing workflows.\u003c\/p\u003e\n\n\u003ch2\u003eProduct Overview\u003c\/h2\u003e\n\n\u003cp\u003eThe Arducam B0184 \/ B0188 IMX219 Low Distortion Camera Module represents a significant advancement in embedded vision technology by combining the proven Sony IMX219 sensor with Arducam's proprietary low-distortion lens design. The module operates on the CSI-2 interface standard, delivering raw image data at 30 frames per second in full 8-megapixel resolution with exceptional color accuracy and dynamic range. The low-distortion optics employ multi-element lens arrays with precision-ground glass elements and anti-reflective coatings, reducing geometric distortion to below 2 percent across the entire field of view, compared to 10-15 percent distortion found in standard modules. This makes it ideal for applications requiring accurate spatial measurements and consistent image calibration across thousands of frames.\u003c\/p\u003e\n\n\u003cp\u003eThe module integrates seamlessly with both Raspberry Pi single-board computers and NVIDIA Jetson Nano development platforms through identical CSI ribbon cable connectors, requiring zero hardware modifications. The Sony IMX219 sensor features a 1\/4-inch optical format with 3280 x 2464 pixel resolution, delivering exceptional low-light performance through its advanced pixel architecture and on-chip analog-to-digital conversion. The module supports multiple output formats including RAW Bayer, YUV, and RGB, with configurable frame rates from 1 to 30 fps, enabling developers to optimize power consumption and processing bandwidth based on specific application requirements.\u003c\/p\u003e\n\n\u003ch2\u003eKey Specifications\u003c\/h2\u003e\n\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003eSpecification\u003c\/td\u003e\n\u003ctd\u003eDetails\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eProduct Type\u003c\/td\u003e\n\u003ctd\u003eCSI-2 Camera Module with Low-Distortion Optics\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eBrand\u003c\/td\u003e\n\u003ctd\u003eArducam\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eModel\u003c\/td\u003e\n\u003ctd\u003eB0184 \/ B0188\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eSensor\u003c\/td\u003e\n\u003ctd\u003eSony IMX219 CMOS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eResolution\u003c\/td\u003e\n\u003ctd\u003e8 Megapixels (3280 x 2464)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eOptical Format\u003c\/td\u003e\n\u003ctd\u003e1\/4-inch\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFocal Length\u003c\/td\u003e\n\u003ctd\u003e3.04mm with low-distortion correction\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eField of View\u003c\/td\u003e\n\u003ctd\u003e160 degrees horizontal diagonal\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eMaximum Frame Rate\u003c\/td\u003e\n\u003ctd\u003e30 fps at full resolution\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eDistortion\u003c\/td\u003e\n\u003ctd\u003eLess than 2 percent geometric distortion\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eInterface\u003c\/td\u003e\n\u003ctd\u003eCSI-2 Ribbon Cable (compatible with Raspberry Pi and Jetson Nano)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eOutput Formats\u003c\/td\u003e\n\u003ctd\u003eRAW Bayer, YUV420, YUV422, RGB565, RGB888\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePower Consumption\u003c\/td\u003e\n\u003ctd\u003eApproximately 200mA at 3.3V\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eOperating Temperature\u003c\/td\u003e\n\u003ctd\u003e-20 to 70 degrees Celsius\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eOrigin\u003c\/td\u003e\n\u003ctd\u003eOriginal\/Authentic\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eWarranty\u003c\/td\u003e\n\u003ctd\u003e7 days on manufacturing defects\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eShipping\u003c\/td\u003e\n\u003ctd\u003e1-5 days from Bengaluru\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eDelivery\u003c\/td\u003e\n\u003ctd\u003e7-8 days across India\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eSupport\u003c\/td\u003e\n\u003ctd\u003e24\/7 via Email and WhatsApp\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eKey Features\u003c\/h2\u003e\n\n\u003cul\u003e\n\u003cli\u003eLow-Distortion Optics: Advanced multi-element lens design reduces geometric distortion below 2 percent, enabling accurate spatial analysis and precise object localization for computer vision applications requiring sub-pixel accuracy\u003c\/li\u003e\n\u003cli\u003eSony IMX219 Sensor: High-performance CMOS sensor with 8-megapixel resolution, excellent low-light sensitivity, and wide dynamic range supporting professional-grade image capture in varied lighting conditions\u003c\/li\u003e\n\u003cli\u003eDrop-In Compatibility: Identical CSI-2 connector and pinout to Raspberry Pi V2 and Jetson Nano cameras, requiring zero hardware modifications for seamless integration into existing projects\u003c\/li\u003e\n\u003cli\u003eMultiple Output Formats: Supports RAW Bayer, YUV, and RGB output modes with configurable frame rates from 1 to 30 fps, enabling optimization for specific processing pipelines and power budgets\u003c\/li\u003e\n\u003cli\u003eCompact Form Factor: Lightweight design with standard camera module dimensions, ideal for embedded robotics, drone vision systems, and space-constrained industrial inspection applications\u003c\/li\u003e\n\u003cli\u003eWide Operating Range: Functions reliably across -20 to 70 degrees Celsius temperature range with consistent optical performance, suitable for both indoor laboratory environments and outdoor field deployments\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2\u003eApplications and Use Cases\u003c\/h2\u003e\n\n\u003cul\u003e\n\u003cli\u003eAutonomous Mobile Robotics: Deploy in ROS-based robot navigation systems where low-distortion imaging ensures accurate visual odometry, obstacle detection, and SLAM (Simultaneous Localization and Mapping) algorithms with minimal calibration drift over extended operation periods\u003c\/li\u003e\n\u003cli\u003eMachine Learning and Computer Vision: Integrate with TensorFlow Lite and PyTorch models on Raspberry Pi and Jetson Nano for real-time object detection, facial recognition, and pose estimation with reduced preprocessing overhead due to superior image quality\u003c\/li\u003e\n\u003cli\u003eIndustrial Quality Inspection: Utilize in automated visual inspection systems for PCB defect detection, component verification, and dimensional measurement where low distortion enables reliable pixel-based measurements without complex calibration matrices\u003c\/li\u003e\n\u003cli\u003eDrone and Aerial Imaging: Implement in lightweight UAV systems for precision agriculture, infrastructure monitoring, and thermal mapping where the compact form factor and low power consumption extend flight time while maintaining image fidelity\u003c\/li\u003e\n\u003cli\u003eMedical and Scientific Imaging: Deploy in portable diagnostic imaging systems and laboratory microscopy setups where optical accuracy and consistent calibration across multiple units ensure reproducible results and reliable data analysis\u003c\/li\u003e\n\u003cli\u003eSmart Surveillance and Security: Configure in edge-computing security systems running on Jetson Nano for real-time threat detection and activity recognition with superior image clarity reducing false positives in crowded environments\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2\u003eHow to Use\u003c\/h2\u003e\n\n\u003cp\u003eTo integrate the Arducam B0184 \/ B0188 IMX219 Low Distortion Camera Module with your Raspberry Pi or Jetson Nano, first ensure the device is powered off and the CSI camera port is accessible. Gently lift the ribbon cable connector clip on the CSI port, insert the camera module's ribbon cable with the blue side facing toward the Ethernet port on Raspberry Pi or away from the USB ports on Jetson Nano, and press the connector clip downward until it clicks securely. Enable the camera interface through raspi-config on Raspberry Pi or through Jetson Nano's device tree configuration, then verify detection using command-line tools such as vcgencmd get_camera on Raspberry Pi or v4l2-ctl --list-devices on Jetson Nano.\u003c\/p\u003e\n\n\u003cp\u003eFor optimal performance, install Arducam's Python libraries and camera control software available on their GitHub repository, which includes calibration tools for leveraging the low-distortion optics in your computer vision pipeline. Configure camera parameters such as resolution, frame rate, and output format through the provided API based on your application requirements. For machine learning applications, capture calibration images of checkerboard patterns using the module's RAW output format, then apply OpenCV's camera calibration functions to generate intrinsic and distortion coefficient matrices specific to your setup. Test the camera feed using ffplay or gstreamer pipelines to verify image quality before deploying in production systems. Refer to Arducam's comprehensive documentation and community forums for advanced configurations including HDR imaging, custom ISP tuning, and integration with popular frameworks like ROS and TensorFlow.\u003c\/p\u003e\n\n\u003ch2\u003eFrequently Asked Questions\u003c\/h2\u003e\n\n\u003cdetails\u003e\n\u003csummary\u003eWhat is the main difference between the Arducam B0184 \/ B0188 and standard Raspberry Pi V2 cameras?\u003c\/summary\u003e\n\u003cp\u003eThe primary difference is the low-distortion optical design. While standard Raspberry Pi V2 cameras exhibit 10-15 percent barrel distortion, the Arducam B0184 \/ B0188 reduces distortion below 2 percent through multi-element lens arrays with precision-ground glass elements and anti-reflective coatings. This makes it significantly superior for computer vision applications requiring accurate spatial measurements, object localization, and consistent image calibration. The module uses the same Sony IMX219 sensor but with Arducam's proprietary lens correction algorithms, making it ideal for SLAM, autonomous navigation, and industrial inspection systems where optical accuracy is critical.\u003c\/p\u003e\n\u003c\/details\u003e\n\n\u003cdetails\u003e\n\u003csummary\u003eIs the Arducam B0184 \/ B0188 fully compatible with Raspberry Pi and Jetson Nano?\u003c\/summary\u003e\n\u003cp\u003eYes, the Arducam B0184 \/ B0188 is a true drop-in replacement for both Raspberry Pi V2 and Jetson Nano cameras. It uses the identical CSI-2 ribbon cable connector and pinout, requiring zero hardware modifications. Simply disconnect the original camera module and connect the Arducam module using the same CSI port. The module is immediately recognized by both platforms and works with existing camera software libraries including picamera for Raspberry Pi and gstreamer for Jetson Nano. No driver installation is required as it operates through standard V4L2 (Video for Linux 2) interfaces.\u003c\/p\u003e\n\u003c\/details\u003e\n\n\u003cdetails\u003e\n\u003csummary\u003eCan I use the Arducam B0184 \/ B0188 for 3D reconstruction and structure-from-motion applications?\u003c\/summary\u003e\n\u003cp\u003eAbsolutely. The low-distortion optics make this module excellent for 3D reconstruction, structure-from-motion, and photogrammetry applications. The reduced geometric distortion below 2 percent means you can use simpler camera calibration models and achieve more accurate 3D point clouds with fewer calibration images. For optimal results, capture a calibration sequence using the module's RAW output format with OpenCV's checkerboard detection, generate intrinsic and distortion coefficients, and apply these parameters in your SfM pipeline. The module's 30 fps capability at full 8-megapixel resolution enables real-time 3D scanning applications on Jetson Nano with TensorRT acceleration.\u003c\/p\u003e\n\u003c\/details\u003e\n\n\u003cdetails\u003e\n\u003csummary\u003eWhat output formats does the camera module support?\u003c\/summary\u003e\n\u003cp\u003eThe Arducam B0184 \/ B0188 supports multiple output formats including RAW Bayer (for maximum processing flexibility), YUV420, YUV422, RGB565, and RGB888. RAW Bayer output is recommended for applications requiring maximum image quality and custom ISP (Image Signal Processing) pipelines. YUV formats offer good compression efficiency for real-time streaming, while RGB formats are ideal for direct integration with computer vision libraries like OpenCV. Frame rates are configurable from 1 to 30 fps depending on the selected output format and resolution, allowing optimization for specific processing bandwidth and power\n\u003c\/p\u003e\u003c\/details\u003e\n\u003ch2\u003eBuy Arducam B0184 \/ B0188 IMX219 Low Distortion Camera Module-drop-in replacement for Raspberry Pi V2 Camera and Jetson Nano Camera Online in India\u003c\/h2\u003e\n\u003cp\u003ePurchase the \u003cstrong\u003eArducam B0184 \/ B0188 IMX219 Low Distortion Camera Module-drop-in replacement for Raspberry Pi V2 Camera and Jetson Nano Camera\u003c\/strong\u003e online at \u003ca href=\"https:\/\/theengineerstore.in\"\u003eThe Engineer Store\u003c\/a\u003e, India's trusted source for genuine electronics. We deliver across Bengaluru, Mumbai, Delhi, Chennai, Hyderabad, Pune, Kolkata, Ahmedabad, Jaipur, and Surat.\u003c\/p\u003e\n\u003cp\u003eOur team in Bengaluru is available 24\/7 to support your journey from product selection to project completion.\u003c\/p\u003e","brand":"My Store","offers":[{"title":"Default Title","offer_id":43856804348067,"sku":"TES-EV00082078","price":1262.78,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0628\/4479\/7091\/products\/B0184-228x228.jpg?v=1704280795","url":"https:\/\/www.theengineerstore.in\/hi\/products\/arducam-b0184-b0188-imx219-low-distortion-camera-module-drop-in-replacement-for-raspberry-pi-v2-camera-and-jetson-nano-camera","provider":"The Engineer Store","version":"1.0","type":"link"}