calibratietargets

Calibratietargets (calibration targets) are reference objects used to establish and verify the accuracy of measurements produced by sensing systems such as cameras, scanners, and LiDAR. By providing known, quantifiable properties—geometric dimensions, color values, or surface reflectance—they enable the calibration of sensor parameters and validation of measurement results. They are widely used across fields including photography, computer vision, robotics, manufacturing, surveying, and quality control.

Common forms include color calibration targets (color checkers and grayscale patches), geometric calibration patterns (checkerboard, dot grids, circle grids) for camera intrinsic and extrinsic calibration, and 3D targets (ball plates, cube arrays) for multi‑sensor alignment. Radiometric and reflectance targets are used to calibrate brightness and color response, while outdoor or large-scale targets support field calibration for machine vision and mapping. In robotics and SLAM, specialized targets aid aligning camera and LiDAR frames.

Procedure: Place target in stable lighting, capture multiple images from varied viewpoints, extract known features, and compute calibration parameters with software tools. The process yields intrinsic camera parameters (focal length, optical center, distortion) and extrinsic parameters (pose relative to the scene), or sensor-to-sensor transforms. Calibration may be repeated to monitor drift or after hardware changes.

Best practices include uniform lighting, known distances and angles, using standardized targets from reputable vendors, and recording conditions for traceability. Many ecosystems provide widely used targets and software, such as checkerboard patterns in OpenCV or color targets like the X-Rite ColorChecker. Properly maintained calibration targets should be kept clean and free of deformities to ensure accuracy.