64-bit architectures such as the ARM Cortex A53 are increasingly becoming the standard. The use of DragonBoard is just as widespread. Due to its compact dimensions and low energy consumption, the board can be used in embedded systems, especially in all conceivable smart devices such as cameras and handhelds - for personal computing as well as in operational production and logistics processes.
MVTec's standard image processing software HALCON has now also been successfully tested on the DragonBoard using the board's native 64-bit instruction set. The tests were performed on a DragonBoard with a quad-core ARM Cortex A53 processor. Compared to 32-bit ARMv7 code running on the same hardware, the 64-bit operating mode of the ARM Cortex A53 processor can speed up image processing algorithms, such as shape-based matching, by up to 40 percent. With the availability of HALCON for Embedded for DragonBoard, high-performance machine vision applications can take full advantage of the 64-bit ARMv8 architecture. MVTec offers to port HALCON for Embedded to customer hardware upon request, taking into account customers' specific requirements.
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By porting HALCON to DragonBoard, MVTec is taking into account the growing importance and spread of 64-bit processors. Customers can contact us with their very specific requirements. We then provide them with a solution that is precisely tailored to their needs. Companies can thus significantly accelerate their image processing processes.
Certain applications can also increase their performance impressively on mobile devices. Examples include smartphone-based identification of components, which simplifies processes such as the maintenance of industrial plants and thus saves costs.
HALCON 20.11 STEADY – IS THERE FOR YOU
HALCON 20.11 brings optimizations for a number of core technologies like surface-based and shape-based matching. With "DotCode", a new 2D code type has been added and with another new feature called "Deep OCR", MVTec introduces a holistic deep-learning-based approach for optical character recognition (OCR).
BUT THAT’S NOT ALL! With "deep learning edge extraction", HALCON 20.11 also brings a new and unique method to robustly extract edges. Especially for scenarios where a variety of edges is visible in an image, or when dealing with low contrast and high noise, deep learning edge extraction outperforms conventional edge extraction filters.