MVTec HALCON 23.05

 Release Notes for HALCON 23.05.0.0 Progress

This document provides the release notes for MVTec HALCON 23.05.0.0 Progress, as released in May2023.
Contents

    Major New Features of HALCON 23.05.0.0 Progress
        Deep Counting
        Training for Deep OCR
        Training for 3D Gripping Point Detection
        Easy Extensions Interface
    Compatibility
        Licenses
        HALCON Library
        HALCON Applications
        Image Acquisition Interfaces
        Digital I/O Interfaces
        Extension Packages
        Further Compatibility Information
    Supported Operating Systems
        Windows
        Linux
    Detailed Description of Changes in HALCON 23.05.0.0 Progress
        HDevelop
            New Functionality
            Bug Fixes
            HDevelop Example Programs
        HDevEngine
            Functionality
            Bug Fixes
        HALCON Library
            Speedup
            New Functionality
            Bug Fixes
        Procedures
        HALCON/PYTHON
        HALCON Variable Inspect
        Extension Packages
        Image Acquisition Interfaces
        Digital I/O Interfaces
        Documentation
        Installation
        Miscellaneous

Major New Features of HALCON 23.05.0.0 Progress
Deep Counting

With Deep Counting, a feature is available to customers as of HALCON 23.05 that can be used to count a large number of objects quickly and robustly as well as to detect their position. The deep-learning-based technology offers significant advantages over existing machine vision methods: The feature can be deployed very quickly, since only very few objects need to be labeled and trained – both steps can be easily done within HALCON. The technology provides reliable results even for objects of highly reflective and amorphous material. With Deep Counting, large numbers of objects such as glass bottles, tree trunks, or food can be counted.
Training for Deep OCR

Deep OCR reads texts in a very robust way, even regardless of their orientation and font. For this purpose, the technology first detects the relevant text within the image and then reads it. With HALCON 23.05, it’s now also possible to fine-tune the text detection by retraining the pretrained network with application-specific images. This provides even more robust results and opens new application possibilities. For example: the detection of text with arbitrary printing type or unseen character types as well as an improved readability in noisy, low contrast environments.
Training for 3D Gripping Point Detection

3D Gripping Point Detection can be used to robustly detect surfaces on any object that is suitable for gripping with suction. In HALCON 23.05, there is now the possibility to retrain the pretrained model with own application-specific image data. The grippable surfaces are thus recognized even more robustly. The necessary labeling is done easily and efficiently via the MVTec Deep Learning Tool.
Easy Extensions Interface

With the help of HALCON extension packages, the integration of external programming languages is possible. The advantage for customers: Functionalities that go beyond pure image processing can thus be covered by HALCON. In HALCON 23.05, the integration of external code has become much easier with the Easy Extensions Interface. This allows users to make their own functions written in .NET code usable in HDevelop and HDevEngine in just a few steps, while benefiting from the wide range of functionalities offered by the .NET framework. Even the data types and HALCON operators known from the HALCON/.NET language interface can be used. This increases both the flexibility and the application possibilities of HALCON.

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