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The Frankfurt-based PIV argues that Industry 4.0 would be virtually blind without the imaging industry . Processes for identifying and interpreting images are indeed indispensable, from driverless cars through biometric person identification: Cameras and related equipment record the relevant images and AI-based image analysis tools subsequently interpret the pictures. In Industry 4.0, such systems are used to, for example, assess the surface quality of workpieces, while ‘seeing’ cobots render the collaboration between machine and human significantly safer. ‘Seeing’ machines also offer clear advantages when it comes to the automation of repetitive, monotonous tasks.

AI-based image processing owes its significant progress in recent years to deep learning , a machine learning process in which multiple levels of neural networks are used in combination and which – in the same way as humans learn – improves by trial and error.

The European Machine Vision Association (EMVA) – a non-profit organization that has been dedicated to the development and use of machine vision technologies since 2003 – also wants to exploit the potential harbored in machine vision. The organization counts both commercial enterprises and research institutes among its members, including several of the 69 institutes that belong to the Fraunhofer Society .