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Home » Authors » Johannes Hiltner

Articles by Johannes Hiltner

Deflectometry

Machine Vision: Inspecting Reflective Surfaces with Deflectometry

Reliable detection of even the tiniest scratches.
Johannes Hiltner
December 5, 2019

Machine vision processes have become standard practice in quality assurance. Inspecting reflective surfaces, however, presents a challenge. A technology known as deflectometry can be used to reliably detect all types of defect even in these circumstances.


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Machine vision plays a key role in highly automated production processes.

Self-learning Intelligence for Object Recognition

More and more, advanced artificial intelligence technologies are being incorporated into machine vision systems.
Johannes Hiltner
July 1, 2019

Machine vision is a key technology for highly automated and seamlessly networked processes in the context of Industry 4.0, a.k.a. the Industrial Internet of Things. The use of new artificial intelligence processes such as deep learning is gaining in importance. A great many benefits make the technology attractive, but it also has limitations.


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Hyperspectral imaging

A Precise Look under the Surface

How hyperspectral imaging is setting the trend in quality assurance.
Johannes Hiltner
September 4, 2018

Hyperspectral imaging allows us to look deep under the surface of objects. Machine vision, in particular, uses this innovative camera technology and thus paves the way for entirely new possibilities in quality management. This benefits a wide range of industries, such as food and beverages, agriculture, and pharmaceuticals.


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Photo 1: OCR software reliably recognizes number combinations and letters.

Reliable Identification with Deep Learning

Deep learning optimizes text recognition in machine vision.
Johannes Hiltner
September 1, 2017

Optical character recognition (OCR) is an important technique in industrial environments. After all, machine vision makes it possible to reliably identify workpieces and products throughout the entire value chain based on printed or stamped characters. 


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