Canonical Recognition Component

Accelerate your downstream processes ensuring efficiency and effectiveness in the entire manufacturing lifecycle

When it comes to geometry simplification, usage of direct modeling manipulation tools, efficient coordinate measuring you can’t but resort to analytical form of geometry. However, it is not always easy if someone works with NURBS modeling or representation software. Leveraging its state-of-the-art technologies and accumulated experience in 3D, Open Cascade comes with Canonical Recognition SDK, which provides applications with the capability of converting NURBS geometries of shapes (B-Spline / drawings with Bezier curves and surfaces) to their analytical form (primitive curves and surfaces). By preserving the topological structure of the original shape, the conversion is made with maximum definition, accuracy and speed. The Canonical Recognition SDK is an indispensable tool for algorithms implemented or best fitted to work on canonical geometry:
  • Surfaces and curves simplification for a better usability in downstream applications (for IP protection, preparation of 3D data for AR or VR, large assemblies visualization)
  • CAM software for accurate calculation of work tools trajectory
  • Manipulations on direct modeling
  • Coordinate measurements machines
Within applications Canonical Recognition SDK can be optimally used after importing neutral (IGES, STEP) or proprietary (DXF, ACIS, Parasolid) files or in other preparatory modules before using special algorithms.


  • Improvement in performance and robustness of numeric algorithms (intersection, projection, etc.)
  • Software compensation of geometric errors in coordinate measuring
  • Seamless integration into Open CASCADE Technology-based applications as a part of CAD data import / export process or as a separate function accessible via GUI.
  • No third-party licensing

Successful implementations

Canonical Recognition SDK is used in CAD Processor — Open Cascade’s proprietary software solution allowing preparation and simplification of 3D reference data for dedicated downstream applications. Canonical recognition The table below features mapping between the original NURBS and the resulting canonical entities. The result depends on the geometry of the original 3D curve or a surface.  
Origin Result
Bezier curves Line
Bezier surfaces Plane
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