With HALCON 23.11, customers have an additional "cloud-ready" variant of the license server at their disposal. This now makes it possible to license HALCON in the environments of commercial cloud providers as well as in enterprise-owned cloud setups without the need for a hardware dongle, solely through a network connection.
This means that HALCON can now be easily licensed across all cloud solutions. By using HALCON in the cloud, customers can easily benefit from the new possibilities offered by machine vision in the cloud.
Structured light 3D reconstruction
In HALCON 23.11, the structured light model has been enhanced: besides deflectometry, it now also provides precise 3D reconstruction for diffuse surfaces in short cycle times. This enhancement gives users the flexibility to develop their own application-specific 3D reconstruction systems using a pattern projector and a 2D camera. The feature is particularly suitable for applications where precise spatial representations are required.
As a result, the technology is suitable for the optimization of manufacturing processes, quality control, and the precise measurement of various surfaces.
In the new HALCON version, customers now have access to multi-label classification, a new deep learning method that allows the recognition of multiple different classes on a single image. Such classes can encompass various properties of the objects within the image, for example defect types, color, or structure.
In practice, this method can, for instance, reveal the presence of different types of defects in an image, allowing a more detailed classification. Compared to other methods, this deep learning method is faster in processing and the effort for labeling is also lower.
In HALCON 23.11, a number of improvements for existing methods and technologies were implemented. For Global Context Anomaly Detection, a method for detecting complex anomalies, the underlying neural network has been further optimized. This improves the accuracy of anomaly detection without increasing hardware requirements or execution time. In addition, HALCON now utilizes the latest NVIDIA® CUDA® toolkit. This provides users with the opportunity to choose from an even greater range of AI accelerators. For example, the new NVIDIA Jetson OrinTM modules are now supported as well. Finally, several performance optimizations of HALCON's core technologies have been implemented in HALCON 23.11. For example, template matching operators (NCC Matching) now run up to 80% faster on Arm-based systems.
You will find all features of HALCON in this feature overview. If you need more information about the technical data please download the Installation Guide or take a look at our Technical Data pages. If you need advice, how to work with HALCON please see our videos or the documentation.