Introducing HALCON 24.11 Steady
HALCON Steady 24.11 from MVTec Software GmbH provides long-term stability and reliability for industrial machine vision applications that require consistent performance over extended product lifecycles. Designed for production environments where software changes must be carefully controlled, the HALCON Steady release offers a stable version of the powerful MVTec HALCON machine vision library while continuing to deliver proven algorithms and high-performance image processing capabilities.
The Steady release model ensures that integrators and manufacturers can maintain validated systems without frequent software upgrades, reducing the need for repeated requalification and minimising operational risk. HALCON Steady 24.11 provides the same comprehensive set of machine vision tools found in the HALCON platform, including deep learning, 3D vision, measurement, identification, and matching technologies.
Optimised for demanding industrial applications, HALCON Steady supports a wide range of interfaces and hardware platforms, enabling seamless integration into automated inspection systems across industries such as electronics, automotive, logistics and medical technology. With its focus on long-term availability and compatibility, HALCON Steady is an ideal choice for machine builders and system integrators who require dependable vision software throughout the lifecycle of their equipment.
NEW 24.11 HIGHLIGHTS INCLUDE:
Deep 3D Matching
HALCON 24.11 contains a deep-learning-based market innovation for the 3D vision sector, especially for bin-picking and pick-and-place applications.
This feature is particularly robust in determining the exact position and rotation of a trained object, and is characterized by very low parameterization effort and fast execution time. Depending on the accuracy requirements, one or more cost-efficient standard 2D cameras can be used to determine the position. Training is performed exclusively on synthetic data generated from a CAD model.
Out Of Distribution Detection (OOD) for Classification
This new HALCON feature makes it easy to recognize unexpected behavior caused by incorrect classifications in production. As a result, users can take appropriate measures, such as stopping the machine, in a targeted and efficient manner.
When using a deep learning classifier, unknown objects are assigned to one of the classes that the system has learned. This can lead to problems if, for example, the defects or objects themselves are of a type that has never occurred before. The new deep learning feature “Out of Distribution Detection (OOD)” indicates when an object is classified that was not included in the training data. For example, this could be a bottle with a green label if the system was only trained on bottles with red or yellow labels. In such cases, HALCON provides the message “Out of Distribution” together with an OOD score that indicates how much the deviation from the trained classes is.
The OOD score can also be useful when expanding deep learning models with new training images by indicating which of the new images will have the greatest value for the new model. For example, a high OOD score for a new training image indicates a greater deviation from the images already in the network – this means a higher information content and, therefore, greater value for the training.
Preview of the New IDE HDevelopEVO
HALCON 24.11 has a special highlight for all users of HALCON’s own integrated development environment (IDE) HDevelop: a preview of the new IDE HDevelopEVO. This is characterized, among other things, by a more modern, intuitive user interface and an improved editor (i.e., the central programming element). The latter enables faster and more efficient programming and prototyping of machine vision applications.
Users can already extensively test the new development environment in HALCON 24.11. The range of functions of HDevelopEVO will be continuously expanded in the coming releases and it will over time become the standard HALCON development environment.
Improved Shape-based Matching
The new HALCON version makes the “Shape-based Matching” feature, used in many applications, more user-friendly.
This technology is used to find objects fast, accurately, and precisely. HALCON 24.11 includes the new “Extended Parameter Estimation” for this purpose. This allows parameters to be estimated with greater granularity, which significantly speeds up execution in some applications. Extended Parameter Estimation enables this estimation also for users without in-depth machine vision expertise.
Optimised QR Code Reader
The performance of HALCON’s QR Code Reader has been significantly increased.
This is particularly evident under difficult conditions, for example, when many codes need to be found in the image area or many textures in the image complicate the detection. The recognition rate has been increased and the evaluation time has been significantly reduced in demanding scenarios.
HALCON Progress Vs HALCON Steady – What’s the difference?
The HALCON Progress Edition:
Nothing else presents “the power of machine vision” more than MVTec’s HALCON Progress Edition. Thanks to its six-month release cycle, it always offers state-of-the-art-features. HALCON Progress is provided on an annual subscription that automatically renews.
The HALCON Steady Edition:
HALCON Steady offers high compatibility, long-term support and is available as one-off purchase. It receives maintenance updates related to bug fixes. The perfect edition for all those customers whose business model does not require shorter release cycles. Every two years there is a new version.
