HALCON Progress Key Visual shows a Person on a Bike driving fast through a dessert

HALCON 18.11

HALCON 18.11 was released in November 2018. It was officially introduced at VISION 2018 and, amongst other things, includes new AI technologies, specifically from the fields of deep learning and Convolutional Neural Networks (CNNs). To learn about the features of the most current version, click here.

HALCON 18.11 is available in two editions: Steady and Progress. While the latter is available as a subscription with a six-month release cycle, the Steady edition – as successor of HALCON 13 – is offered as one-time purchase.


Below you find an overview over the most prominent features of this release. For a detailed list, please have a look at the release notes.

HALCON in Your Industrial Network

HALCON 18.11 introduces the Hilscher-cifX interface. This allows HALCON to communicate with almost all industrial field bus protocols via Hilscher cards. Among others, CC-Link, EtherCAT, EtherNet/IP, PROFIBUS, and PROFINET are supported.

Deep Learning

Deep Learning in MVTec HALCON

With HALCON 18.11, users are able to train their own classifier using pretrained CNNs (Convolutional Neural Networks) included in HALCON. These networks have been highly optimized for industrial applications and are based on hundreds of thousands of images. HALCON 18.11 offers a seamlessly integrated, comprehensive set of deep learning functions for

  • classifying entire images
  • object detection
  • semantic segmentation.

Learn more about Deep Learning with HALCON on this page.

Handle Variable Inspect in HDevelop

With HALCON 18.11, HDevelop can display detailed information on most important handle variables. This allows developers to easily inspect the current properties of complex data structures at a glance, which is extremely useful for debugging.

Find more information on this page.

New Data Structure "Dictionaries"

dictionaries icon

HALCON 18.11 introduces a new data structure "dictionary", which is an associative array that opens up various new ways to work with complex data.

For example, this allows bundling various complex data types (e.g., an image, cor­re­spond­ing ROIs and parameters) into a single dictionary, making it easier to structure programs when, e.g., passing many parameters to a procedure.