FusionENG has developed its own 2D DIC (Digital Image Correlation) solution, which enables accurate quantification of displacement and strain fields by using a single-camera.

By applying speckle patterns, sub-pixel correlation (ZNSSD), and multi-resolution tracking, this system maintains stability even under lighting variations and portional noise. Graphic libraries such as OpenCV, CAD, and Nevron are used to integrate image–geometry alignment, annotation, and CAD overlay into a unified pipeline.

• Core Tracking Algorithm : Based on OpenCV Optical Flow (Pyramidal Lucas–Kanade), enhanced with outlier removal, normalization, and temporal smoothing for robust performance under motion or illumination changes.
• Calibration and Coordinate Conversion : Includes camera/lens calibration, distortion correction, and planar homography to accurately convert pixel coordinates to real-world coordinates, yielding a precise mm-per-pixel scale.
• Visualization and Analysis : Generates contour/vector maps, ROI masking, virtual extensometers, and path/area statistics, providing multiple visualization and analysis outputs.

This solution is applicable to laboratory and field well. Users are also provided with OpenCV-based Python programming training, enabling them to directly customize and automate analysis workflows.

Development of a 3D DIC version is currently in progress, aiming to extend capability toward spatial deformation and volumetric strain analysis.