MVTec Software GmbH Releases the New Version of the MERLIC 5 Software

By Tiera Oliver

Associate Editor

Embedded Computing Design

October 08, 2021


MVTec Software GmbH Releases the New Version of the MERLIC 5 Software

MVTec Software GmbH released MERLIC 5, the new version of its all-in-one machine vision software. The software is designed to enable complete machine vision applications to be created without having to write a single line of code.

The highlights of the new MERLIC 5 release include modern deep learning features and improved camera handling. Along with the latest release, MVTec also offers a new licensing model for maximum flexibility which allows customers to choose whatever best meets their requirements from a range of different packages and price categories.

"With MERLIC 5, we offer high-quality yet easy-to-use machine vision software for all conceivable applications and industrial sectors. It allows our customers to conveniently integrate a machine vision package into their process environment and access innovative deep learning technologies," explains Christoph Wagner, Technical Product Manager for MERLIC at MVTec.

MERLIC 5 contains new and optimized features including the improved camera handling using the Image Source Manager (ISM), which separates the image acquisition source from the image processing part. As a result, machine vision applications can be copied and run between different systems without adjusting the camera settings. The graphical user interface allows the image sources to be comfortably managed and configured.

In addition, the release of the new version means that MVTec's latest deep learning functions are now also available in the MERLIC 5 all-in-one machine vision software. Among other things, MERLIC 5 includes deep-learning-based anomaly detection, which provides added value, particularly in applications where few or no “bad images” are available. Per the company, just a small number of "good images" is sufficient for training so that all types of defects can then be located reliably and precisely. The training process usually takes only a few seconds, meaning that users can perform many iterations to fine-tune their applications within a short period of time.

The second deep learning feature integrated into MERLIC 5 is the "classify image" tool. This tool can be used to assign images to trained classes based on deep learning algorithms. The technology is particularly suitable for classifying defects or objects with highly variable shapes and appearance, as in the case of natural products. The models can be trained using, among other things, the free Deep Learning Tool from MVTec and then imported into MERLIC 5.

The MERLIC 5 launch will be accompanied in its early phase by a campaign to generate curiosity about its deep learning features and also to help users understand them better.

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Tiera Oliver, Associate Editor for Embedded Computing Design, is responsible for web content edits, product news, and constructing stories. She also assists with newsletter updates as well as contributing and editing content for ECD podcasts and the ECD YouTube channel. Before working at ECD, Tiera graduated from Northern Arizona University where she received her B.S. in journalism and political science and worked as a news reporter for the university’s student led newspaper, The Lumberjack.

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