Major features of HALCON 24.05

This version again brings some improvements as well as new features, such as the first iteration of the extended parameter estimation for Shape Matching. The new HALCON release also includes a new version of the OpenVINO™ Toolkit AI² plug-in, speedups and further improvements.

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Extended parameter estimation for Shape Matching

HALCON 24.05 introduces the first iteration of the extended parameter estimation for Shape Matching. With its subpixel accuracy, Shape Matching finds objects robustly and accurately in real-time, even in the most challenging situations. Thanks to the extended parameter estimation, manual parameter adjustments will soon be a thing of the past. Using multiple annotated images, users can now easily optimize for maximum online speed while keeping robustness through automated parameter tuning. Users thus benefit from a faster implementation of shape matching applications, even without specialized expertise. Shape Matching has never been easier!

Bar code reader improvements for stacked bar codes

The bar code reader for GS1 DataBar Expanded Stacked codes has been improved in HALCON 24.05. Depending on the application, customers can expect significant improvements to their decoding rates. This will especially benefit industries such as logistics, retail, and manufacturing, where stacked bar codes are an essential means of tracking and tracing goods.  

3D improvements & enhancements: Importing 3D object models from the STEP format

Starting with version 24.05, HALCON supports the STEP (Standard for the Exchange of Product Data) file format, the industry standard for 3D CAD data. Customers can now seamlessly load STEP CAD data directly into a HALCON 3D object model without any intermediate steps or conversions. The STEP format is supported by most common CAD programs, increasing interoperability and efficiency, because models for 3D matching can be taken directly from the planning data in the CAD software. 

New version of the OpenVINO™ Toolkit AI² plug-in

Parallel to the HALCON 24.05 release, a new version of the OpenVINO Toolkit AI² plug-in will be released. This update uses the latest LTS version of the Intel® Distribution of OpenVINO™ Toolkit, ensuring compatibility with the latest Intel hardware and boosting the inference performance of deep learning applications. Notably, the new plug-in version enhances support for Intel’s 13th generation of Core processors, leading to improved inference performance. In addition, customers can now also utilize Intel’s discrete graphics cards for inference, providing greater flexibility in selecting the appropriate hardware for their application. 

Speedups and further improvements

HALCON 24.05 also includes several performance optimizations for various core technologies. For example, unwarping byte images using a vector field is now up to 285 % faster on AVX2-capable Intel CPUs. The operator map_image is now up to 25% faster as well. 

In addition, HALCON 24.05 provides adjustments to many operators to address performance impacts resulting from Intel's resolution of the "Downfall" security vulnerability.  

Curious about what's to come?

We will inform you in regularly about the news you can expect in HALCON.