The latest 19.11 update of Halcon Progress contains the cutting edge features you need for truly Deep Learning enhanced machine vision. This latest progress update aims to improve the efficiency of training your machine to label and identify key segments of visual data. This means better detection of defects across a huge variety of manufacturing settings from bottling to pharmaceuticals.

Halcon Anomaly Detection

Anomaly Detection – NEW

Brand new with Halcon 19.11! This new feature allows you to train your machine to from a small number of quality base samples and then identify anomalies with great efficiency. Being able to quickly distinguish anomalous areas means that this latest version is ideal for any application requiring automated surface inspection.  Learn more about Anomaly Detection.


Halcon Generic Box Finder

Generic Box Finder – NEW

Another new that functionality allows the user to find boxes of different sizes based on 3D space, eliminating the need to train a model for each required box size. This greatly the improves the efficiency of any task involving a variety of different box sizes.

Halcon Semantic Segmentation

Semantic Segmentation

By utilising semantic segmentation, trained defect classes can be localized to within pixel accuracy. This allows a machine to solve inspection tasks that previously could not only with significantly more programming effort.

Halcon Object Detection

Object Detection

Object detection localizes trained object classes and identifies them with a surrounding rectangle (axis-alligned as well as oriented bounding boxes). Touching or partially overlapping objects are also separated, enabling object counting.

 

 

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