MVTec Software GmbH
 

Newest HALCON Features

On this page, you will find information on the newest features of MVTec's standard machine vision software HALCON.

Upcoming Version – HALCON 18.11

HALCON 18.11 software box

In November this year, the next HALCON release HALCON 18.11 will arrive. It will be officially introduced at VISION 2018 and, amongst other things, will include new AI technologies, specifically from the fields of deep learning and convolutional neural networks (CNNs).

HALCON 18.11 will be available in two editions: Steady and Progress. While the latter is available as a subscription with a six-month release cycle, the Steady edition – as successor of HALCON 13 – is offered for regular purchase.

Over the next months, we will grant you a sneak peek at some of HALCON 18.11's features here – so be sure to check back regularly!

Feature Preview

Preview of HALCON 18.11 Features

New Data Structure "Dictionaries"

dictionaries icon

HALCON 18.11 will introduce a new data structure "dictionary", which is an associative array that opens up various new ways to work with complex data.

For example, this allows bundling various complex data types (e.g., an image, corresponding ROIs and parameters) into a single dictionary, making it easier to structure programs when, e.g., passing many parameters to a procedure.

Dictionaries can also be read from and written to a file. This allows an engineer to bundle all information necessary to reproduce a certain application's state (e.g., camera calibration settings, defective images, and machine parameters) into a single file. This file can then easily be shared with an machine vision expert for offline-debugging.

Handle Variable Inspect in HDevelop

datacode handle inspect HALCON 18.11

With HALCON 18.11, HDevelop can display detailed information on most important handle variables. This allows developers to easily inspect the current properties of complex data structures at a glance, which is extremely useful for debugging.

Double-clicking a handle variable now returns all parameters associated with the handle and their current settings. For example, the user can now easily examine parameters of a data code handle, such as "polarity", "symbol type" or "finder pattern tolerance", as well as complex parameters that carry multiple key-value pairs, like for example the camera parameter of a 3D shape model handle.

HALCON 18.05 – Current Version

The latest HALCON version was released on May 22, 2018 and – reflecting the release date – it is named: HALCON 18.05. Below, you can find the major features included in this version.

 

Download HALCON & Try it for free View the HALCON 18.05 leaflet

CPU Inference

With HALCON 18.05, customers are able to perform deep learning inference on a CPU

Deep learning inference performing on CPUs

This CPU inference has been highly optimized for Intel®-compatible x86 CPUs. In tests, this resulted in a typical inference execution time on a standard Intel CPU (8 threads) that achieves performance similar to a midrange GPU.

Removing the need for a dedicated GPU greatly increases the operational flexibility. E.g., industrial PCs that usually are not designed for housing large and powerful GPUs can now easily be used for deep-learning-powered classification (inference).

Improved Bar Code Reader

Bar code reading has been improved

HALCON 18.05 features optimized edge detection, which improves the ability to reliably read bar codes with very small line widths as well as strongly blurred codes. Moreover, the quality of the bar codes is also verified in accordance with the most recent version of the ISO/IEC 15416 standard.

Enhanced Deflectometry

Enhanced deflectometry functionality

The deflectometry functionality introduced in HALCON 17.12 now includes a new pattern type that improves the precision and robustness of error detection especially on partially specular surfaces like varnished metal sheets.

3D Improvements

HALCON 18.05 offers optimized functions for surface-based 3D matching. These can be used to determine the position of objects in 3D space more reliably, making development of 3D applications easier. In addition, HALCON now also includes a new helper procedure that allows developers to quickly inspect and debug parameters and results of a surface-based matching application.

Automatic Handle Clearing

HALCON 18.05 also makes it much more comfortable to work with handles by clearing these automatically once they are no longer required. This significantly reduces the risk of creating memory leaks and makes writing "safe code" much simpler.

Support for Hypercentric Lenses

HALCON supporting images recorded by hypercentric lenses
The object to be inspected and the image acquired with a hypercentric lense

A new camera model within HALCON now allows the corrections of distortions in images that were recorded with hypercentric (also known as pericentric) camera lenses. These lenses can depict several sides of an object simultaneously, thus enabling a convergent view of the test object. With this technology, users only need a single camera system for inspection and identification tasks, e.g., the inspection of cylindrical objects.

HDevEngine Improvements

The HDevelop library export feature has been expanded: Developers can now access HDevelop procedures not just in C++, but also in .NET via an exported wrapper – as easily and intuitively as a native function. This significantly facilitates the development process.

Previous Version – HALCON 17.12

HALCON 17.12 was the first release of the HALCON Progress Edition. To learn more about the different HALCON editions, please click here.

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 robustly reading touching characters
Automatic text reader
Surface fusion for multiple 3D point clouds
Surface fusion

Automatic Text Reader

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

HALCON now offers a 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.

Previous Version – HALCON 13

To find out more about the numerous features and improvements of our previous version HALCON 13, please click here.

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