Machine vision up close at VISION 2016

20th October 2016
Posted By : Anna Flockett
Machine vision up close at VISION 2016

Showcasing its newest technologies at VISION, the world's leading trade fair for machine vision in Stuttgart, on 8-10th November, MVTec Software will show visitors experiences of highlights in the latest HALCON and MERLIC software releases. Informative demonstrations on texture inspection, matching, deep learning, and the Industrial Internet of Things (IIoT) provide insights into the performance and practical relevance of machine vision features at booth E72 in hall 1.

Also In exciting live sessions, experts will present useful knowledge on how to develop machine vision applications.

HALCON 13: Better performance, robustness, and usability

HALCON 13 is now even more robust when it comes to recognising bar codes and data codes, even when they are damaged, occluded, or incomplete. The performance of shape-based matching has also been improved, and a new feature for user-friendly texture inspection has been added. Enhanced functions for Optical Character Recognition (OCR) based on deep learning technologies round off the new release.

In demonstrative live sessions, MVTec experts will discuss the exciting HALCON 13 feature ‘Debugging of HDevEngine’. The presentation will explain how developers can use HDevEngine in HDevelop to locate and fix programming bugs in the machine vision section of their C# or C++ application.

This new feature simplifies processes for programmers of machine vision applications, resulting in savings in time, cost, and effort. An intermission demonstration will also show three-dimensional augmented reality scenarios using 3D vision technologies.

One presentation at the Industrial Vision Days will outline a variety of applications to demonstrate how to use machine vision with HALCON 13 to automate processes, and how customers can benefit from standard software in particular. 

MVTec will also be showcasing the following exciting topics on their booth:

  • Defect detection in fabric using HALCON’s new easy-to-use texture inspection.
  • Speedup of HALCON's shape-based matching technology using SSE2/AVX2 to identify and count different objects.
  • Human-machine interaction in IIoT scenarios.
  • Application of deep learning approaches in the machine vision segment.

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