Search - MVTec Software

Search within

Deep learning detects defects in the food industry

Automation specialist INNDEO has developed a sophisticated automation solution for quality control in the packaging industry. Thanks to machine vision and deep learning technologies, high speeds and defect detection rates are no longer a problem.

AI-powered machine vision automates quality inspection in the pharmaceutical industry

The pharmaceutical company Aspen is improving the quality inspection of filled ampoules with the MVTec HALCON machine vision software and the consulting and technical support services provided by MVTec. With deep learning methods, the company has significantly increased accuracy and efficiency in its automated inspection process within the pharmaceutical industry.

Full quality control with HALCON´s deep learning functions

One of the key challenges in automated battery production is achieving stable welds without damaging the housing. To meet strict automotive quality standards while reducing costs, Manz AG is developing inline inspection systems that enable full process control – a smart alternative to complex, destructive testing methods.

Simple and reliable control of the number of persons within a building with MVTec HALCON

Strelen Control Systems GmbH is a Certified Integration Partner of MVTec with seat in Büttelborn, close to Darmstadt, Germany. The solutions developed by Strelen are suitable for the inspection and analysis as well as for the automation and regulation of production processes. Their solutions include the development of IIOT (Industrial Internet of Things, aka Industry 4.0) applications and the integration of artificial intelligence in the evaluation of optically obtained data.

Technical University of Applied Sciences Würzburg-Schweinfurt

At Technical University of Applied Sciences Würzburg-Schweinfurt (THWS), Professor Christian Zirkelbach is teaching robotics and machine vision at Faculty of Applied Natural Sciences and Humanities. He has integrated advanced machine vision tools into its robotics curriculum, leveraging MVTec HALCON software since 2019. We’ve talked with him about the most recent project in robotics education.

DCTau: A photographer's tool for testing digital cameras based on HALCON

DCTau by Anders Uschold, Munich, provides a standardized test for evaluating digital cameras with minimal operator input. Designed for both beginners and professionals, it measures resolution, contrast, noise, sharpening, distortion, and brightness loss across all color channels – all implemented in the HALCON environment for quick adaptation to diverse test subjects.

Vision system sorts tomato seedlings - University of Wageningen

The University of Wageningen’s system automates the sorting of tomato seedlings at a rate of up to 18,000 plants per hour. Using ten cameras and 3D modelling, the biomass of each seedling is calculated and classified into quality categories automatically.

Vision Helps Spot Failures on the Rail - Network Rail Ltd.

Network Rail Ltd. uses Omnicom Engineering’s OmniVision system to automatically inspect rail infrastructure for issues such as missing fasteners, faulty welds, or damaged rail heads. MVTec HALCON is employed to analyze image data in real-time and identify potential defects.

MVTec HALCON’s deep learning helps Panasonic Energy to propel automotive battery production

Panasonic Energy manufactures automotive batteries, for which demand is increasing worldwide, at multiple sites in Japan and North America. The company recently implemented MVTec HALCON’s deep learning technologies on a large scale at its Kansas plant in the U.S. to improve yield and quality in the cylindrical lithium-ion battery manufacturing process.

Completely under control: Bin-picking-system allows for better efficiency in the production of differential gears - Jtekt Torsen

Machine vision optimizes quality inspection in automotive production

Consistently high quality is an absolute must in automotive production. To ensure that welded connections in body shells meet these standards, DGH has developed an application that automatically inspects them and identifies anomalies. The MVTec HALCON machine vision software and the MVTec Deep Learning Tool ensure fast and precise inspection processes.

Machine Vision automates and optimizes battery inspection

A variety of defects can occur during battery production. Averna has developed a method for the automated inspection of batteries that reliably detects all conceivable defects. Here, the machine vision software MVTec HALCON plays a key role.