1. HOME
  2. Technology
  3. Morpho Distance Scanner™

Morpho Distance Scanner™

Morpho Distance Scanner™

Use Case

  • Self-driving / On-board camera
  • Target Device
  • Surveillance camera
  • Ship / Train / Airplane
  • Autonomous vehicle
  • Drone
  • Photographic Equipment
  • Wide-angle lens

Function or Purpose

  • Object detection
  • Human detection
  • Image recognition

Morpho Distance Scanner™ is software that estimates the distance to objects from an image captured by a single RGB camera.

Features

  • Distance estimation using just one RGB camera
  • High installation flexibility - no strict camera position or angle calibration required
  • Real-time inference at up to 30 fps

Product Details

Background of Development

As autonomous driving and ADAS (Advanced Driver Assistance Systems) continue to evolve, the number of sensors installed in vehicles is increasing every year. Among these, accurately measuring the distance between a vehicle and surrounding objects is critically important for ensuring safety.
Traditionally, distance estimation has relied on LiDAR or stereo cameras. However, these solutions are costly, making them difficult to deploy in mid-range or lower-priced vehicle segments. They also require additional installation space and may limit vehicle design flexibility.
To address these challenges, Morpho has developed a distance estimation technology that operates using only a single RGB camera. This software-based approach enhances vehicle design flexibility and cost performance while strengthening safety capabilities.

Features

Morpho Distance Scanner™ is software that estimates the distance to objects from a single RGB image. It requires no additional hardware and can utilize existing in-vehicle cameras as they are.

In ADAS and autonomous driving applications, it serves as a new alternative to LiDAR, stereo cameras, sonar, and millimeter-wave radar. It contributes to reducing system costs while enhancing functionality in automotive camera systems.

Because it leverages cameras already installed in vehicles, advanced distance estimation can be introduced without adding new hardware. For OEMs and Tier-1 suppliers seeking to enhance ADAS functions, this solution is easy to implement and ready for immediate deployment.

Beyond automotive applications, this technology also offers strong scalability for use in smartphones, robotics, and other industries.

Key Features

  • Operates with a single RGB camera: Can serve as an alternative to LiDAR, stereo cameras, sonar, and millimeter-wave radar for distance estimation.
  • High flexibility in installation: No strict adjustments to camera position or angle are required.
  • Two models available, depending on application needs:
    • High-precision model (3,000 ms / frame)
    • High-speed model (33 ms / frame)
      (Measurement conditions: Nvidia Jetson AGX Orin)
  • Supports real-time processing: Enables inference at up to 30 fps, suitable for in-vehicle deployment.
  • Ideal for Software-Defined Vehicles (SDV): Functions can be expanded via software updates, enabling integration across a wide range of vehicle types and platforms without hardware modifications.

Top Left: Original Video

Bottom: Distance estimation result (Distance to the object is shown as a heatmap)

Top Right: Bird’s-Eye View (A 15m x 20m bird’s-eye view created from the estimated distance of each pixel. The fact that the bird’s-eye view is not distorted indicates high accuracy of distance estimation. The blue area is the part not visible in the original video.)

Integration with Object Detection

Distance to specific objects detected by Morpho’s object detection technology, Morpho Deep Detector, can also be estimated.

The Format to Provide the Product

Library files and technical documentation for application development are provided to suit your operating environment. Please contact our representative for details.

Webinar

We hold webinars that introduce the basics of image processing and AI technology and key points for their application.
You can watch the webinars we have held so far from the link below.