SHOW PREVIEW: VISION
Deep learning and embedded vision top of agenda
E
mbedded vision and deep learning will be two big talking points at the Vision show in Stuttgart.
Tere will be numerous embedded products
or equipment for embedded systems on display, while MVTec Soſtware, Adaptive Vision, Irida Labs, Stemmer Imaging, Silicon Soſtware and Matrox Imaging will be among the companies exhibiting deep learning technology, a subset of machine learning and artificial intelligence employing neural networks. Powerful embedded computing platforms
like Arm-based system-on-chips (SoCs) are opening up new ways to deploy vision technology. ‘Te Arm-based SoC solutions are becoming increasingly more efficient and can now oſten achieve parity, especially in terms of their price-performance ratio, compared with X86 architectures which are still predominant in the industry environment,’ commented Gerrit Fischer, head of product market management at Basler. Basler will present an embedded vision
development kit at the show, which combines, as a system approach, a Dart camera module with Bcon for a MIPI interface, a Snapdragon 820 Arm processor, and the Pylon camera soſtware suite. ‘Embedded vision systems will probably
become established in every industry, but especially in industrial production. Switching manufacturing to new production concepts, which is being stimulated by the basic idea of Industry 4.0, will call for the use of intelligent systems,’ commented Holger Wirth, vice president of R&D automation at Isra Vision. Isra Vision will present an embedded camera
for robot guidance and 3D position detection during Vision 2018. Te company’s embedded vision systems support standard industrial interfaces based on Ethernet, along with OPC-UA and WLAN. Paul Maria Zalewski, from Allied Vision, said:
‘Especially on the two vertical markets of factory automation and intelligent traffic systems, we are seeing a change towards embedded vision because price pressure on the manufacturers of these systems is increasing and their customers expect increasingly more compact vision systems.’ Embedded vision is also expected to open up
new applications outside of factory automation, according to Christoph Wagner, product manager for embedded vision at MVTec Soſtware.
The Arm-based SoC solutions are becoming increasingly more efficient and can now often achieve parity … with X86 architectures
He said: ‘Many applications involving larger unit numbers are now being implemented on embedded devices, since these devices have many advantages compared with the standard PC variant, for example reduced power consumption, independence of peripherals, and lastly the price and shape factor.’ MVTec will release Halcon 18.11 at the show, which is compatible with 64-bit Arm platforms.
Artificial intelligence Halcon 18.11 will also have deep learning functionality, a powerful tool for certain tasks like classification, although it won’t solve every inspection problem. ‘Te strength of deep learning lies in how its
30 Imaging and Machine Vision Europe • October/November 2018
approach can take more flexible decisions than the sets of predefined rules you find in conventional machine-vision systems,’ stated Volker Gimple, who heads the machine vision group at Stemmer Imaging. ‘Deep learning offers an edge whenever you have test objects with large variations that make them difficult to model mathematically,’ added Dr Klaus-Henning Noffz, managing director of Silicon Soſtware. Today, deep learning is being incorporated
into applications where machine vision handles the classification of the test object in question. Dr Noffz offered an example from automotive manufacturing: ‘With the help of deep learning, self-learning algorithms can detect every single tiny flaw in the paint – even those invisible to the naked eye.’ While a number of hurdles remain in the
application of deep learning – the amount of time necessary for execution and the training of neural networks, for example – companies like Framos are confident that deep learning will dominate virtually every method of classification, such as quality assurance or sorting, in the medium term. Dr Noffz is also a believer: ‘By shiſting the focus from programming to training such systems,
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