The new version implements new features in the areas of deep learning and matching as well as improvements to the subpixel bar code reader, Deep OCR, and the integrated development environment HDevelop. HALCON 21.05 Progress gives users the benefit of even more robust machine vision processes and improved usability.
- HDevelop usability improvements
HDevelop’s new window docking has been improved. Users have now more options to control the position where floating windows are opened.
- Deep OCR improvements
With HALCON 21.05, the performance and usability of Deep OCR have been improved. Big images are now handled more robustly and the result now contains a list of character candidates with corresponding confidence values, which can be used to further improve the recognition results. Customers also benefit from an overall improved stability as well as from the fact that they can address a wider range of possible applications, thanks to additional character support.
- Deep Learning Framework
HALCON 21.05 introduces a first version of the HALCON Deep Learning Framework. This framework allows experienced users to create their own models within HALCON. With this feature, experts can now realize even the most demanding and highly complex applications in HALCON without having to rely on pretrained networks or third-party frameworks.
- Generic Shape Matching
HALCON 21.05 introduces Generic Shape Matching, which makes MVTec's industry-proven shape matching technologies even more user-friendly and future proof. By significantly reducing the number of required operators, users can now implement their solution much faster and a lot easier. Moreover, thanks to the unification of HALCON’s different shape matching methods into a single set of operators, users can now integrate new shape-matching-related features more smoothly.
- Subpixel bar code reader improvements
HALCON’s subpixel bar code reader is capable of reading codes with very thin bars. In HALCON 21.05, the subpixel bar code reader has been improved regarding low-resolved codes. The decoding rate for those can now increase up to 50%.
- Improvements of basic operators in 2d and 3d for fast and robust preprocessing
3D point cloud sampling now supports a new mode called “furthest point”, which typically results in a more uniform sampling of a 3D object. The user sets the number of output points and then iteratively adds to the output object the point of the input object that is furthest from all points already added to the output model. The furthest point mode usually allows a reasonably uniform sampling. The 3D point cloud smoothing has been extended by a new mode that uses information from the XYZ-mappings. 3D point cloud smoothing can be used as a preprocessing step to smooth point clouds and remove noise. This mode usually leads to a much faster processing time.
Further improvements in HALCON 21.05 include general speedups of basic image operators.