HALCON 26.05 New Features | MVRPL

MVRPL - HALCON 26.05 New Features . With HALCON 26.05, automatic contour optimization for shape-based matching (SBM) enables users to automatically remove unstable or misleading contours from SBM models. Reflections, shadows, or random texture often introduce unreliable contours that reduce matching robustness and require labor-intensive manual contour optimization. With the new feature, users simply provide sample images of real object instances. Based on these samples, the system analyzes which contours appear consistently across variations and retains only the stable contours while removing unreliable ones.

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HALCON 26.05 New Features

Automatic contour optimization for shape-based matching


Automatic contour optimization for shape-based matching

With HALCON 26.05, automatic contour optimization for shape-based matching (SBM) enables users to automatically remove unstable or misleading contours from SBM models. Reflections, shadows, or random texture often introduce unreliable contours that reduce matching robustness and require labor-intensive manual contour optimization. With the new feature, users simply provide sample images of real object instances. Based on these samples, the system analyzes which contours appear consistently across variations and retains only the stable contours while removing unreliable ones.

Advanced AI Object Detection

A new generation of deep-learning-based object detection is available with HALCON 26.05, delivering up to 5x faster inference while maintaining high detection accuracy. The new architecture enables efficient detection of objects and is optimized for demanding machine vision scenarios where both speed and precision are critical.

Data Matrix Rectification

HALCON 26.05 expands its code reader with Data Matrix rectification, enabling reliable reading of Data Matrix codes even when they appear on curved or deformed surfaces. In many industrial applications, codes are printed on non-flat materials, which can distort the symbol geometry and reduce reading reliability. With the new rectification capability, HALCON compensates for these distortions before decoding, significantly improving robustness in such scenarios.

Enhanced Data Augmentation

HALCON 26.05 introduces enhanced data augmentation for deep-learning workflows. The new approach replaces the previous procedure-based augmentation and preprocessing steps with configurable operators that integrate directly into HALCON deep-learning pipelines. Users can define augmentation pipelines programmatically, apply transformation techniques such as geometric transforms, color variations, and blurring, and preview the resulting image variations.

HDevelopEvo 26.05 Major Features

HDevelopEVO is continually evolving to meet your needs. It already offers a range of powerful image processing features. With each release, we expand the possibilities.

These are the newest major features for the upcoming release:

.NET interface for the HALCON Script Engine:

Run HDevelopEVO scripts directly in your .NET applications.

HALCONSearch Agent:

Describe your vision task and find the right HALCON operators and example scripts.

Context-aware documentation in the editor:

See file, procedure, and parameter information directly while coding.

Visual prompting for AI assistants:

Include image data directly in your prompts.





To Know More About Machine Vision System in India, Contact Menzel Vision and Robotics Pvt Ltd at (+ 91) 22 35442505 or Email us at info@mvrpl.com



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