Halcon 17.12

MVTec

 

HALCON 17.12 is the first release of the new HALCON Progress Edition

 

Deep Learning out of the Box

Training a CNN

 

With HALCON 17.12, users are able to train their own classifier using CNNs (Convolutional Neural Networks) with HALCON. After training the CNN, it can also be used for classifying new data with HALCON. Click here to learn more about training and using the CNN.

 

 

Inspecting Specular Surfaces with Deflectometry

A camera setup using deflectometry to inspect a specular reflecting object

 

HALCON 17.12 includes new operators, which enable the user to inspect specular and partially specular surfaces to detect defects by applying the principle of deflectometry. This method uses the reflections on specular objects’ surfaces by observing mirror images of known patterns and their deformations on the surface.

 

 

Automatic Text Reader
Automatic text reader robustly reading touching characters

 

HALCON 17.12 features an improved version of the automatic text reader, which now detects and separates touching characters more robustly.

 

 

Surface Fusion For Multiple 3D Point Clouds
Surface fusion for multiple 3D point clouds

 

HALCON now offers a new method that fuses multiple 3D point clouds into one watertight surface. This new method is able to combine data from various 3D sensors, even from different types like a stereo camera, a time of flight camera, and fringe projection. This technology is especially useful for reverse engineering.

 

 

 

HDevEngine Improvements

With the new HDevelop library export included in HALCON 17.12, calling HDevelop procedures from C++ is as easy and intuitive as calling any other C++ function. This new library export also generates CMake projects.