MVTec Software GmbH (www.mvtec.com), a leading international provider of machine vision software, has launched the new version (21.11) of its HALCON machine vision software. This version contains many new and optimized features that can be used to implement machine vision applications even more robustly and professionally in a lot of all industrial sectors. Among other things, the new developments include the addition of instance segmentation to the available deep learning technologies, an improved barcode reader, as well as greater usability for dictionaries and Generic Shape Matching. HALCON 21.11 also comes with a plug-in for the OpenVINO toolkit from Intel. By the time of the release, it will also be possible to use the plug-in for other software products from MVTec.
"With HALCON 21.11, we remain in step with the times. The addition of the comprehensive toolbox sets new machine vision standards for a lot of all industrial sectors. We also keep our promise of delivering crucial added value for users through continuous further developments, advanced features, and short release cycles," explains Mario Bohnacker, Technical Product Manager for HALCON at MVTec Software GmbH.
Combining the benefits of semantic segmentation with those of object detection
One highlight of HALCON 21.11 is the addition of instance segmentation technology to the range of deep learning functions. This technology combines the benefits of semantic segmentation with those of object detection and enables the pixel-precise assignment of objects to different classes. It is particularly useful in applications where objects are very close together, touch each other, or overlap. This is the case, for example, when gripping randomly arranged objects from bins ("random bin picking") and when identifying and measuring naturally grown structures, such as organic material.
MVTec has also improved the barcode reader for the 128/GS1-128 code. Thus, it is now also possible to read codes that are blurred due to movement or when the depth of focus is limited. Code 128/GS1-128 enjoys widespread use and is often employed in logistics, due to its compact size and great data density.
Improved usability, faster application development, and more efficient image processing
Another improved feature has to do with the handling of dictionaries, which can be managed even faster and more easily with HALCON 21.11. The dictionaries can now be used with far fewer operator calls, thus speeding up and simplifying the development process. The same holds for improvements to Generic Shape Matching. Based on customer feedback, the usability was increased, for example by automatically determining many more parameters. This makes the access to MVTec's industry-tested shape matching technologies more user-friendly.
With the HALCON 21.11 release, users of the previous version also benefit from the advantages of Intel's OpenVINO toolkit. The corresponding plug-in which can also be used for other MVTec software products in the future, makes it possible to access AI accelerator hardware that is compatible with the OpenVINO toolkit from Intel. This allows deep learning inference to run much faster on Intel processors, including CPUs, GPUs, and VPUs.