Konrad Häublein

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—In the domain of image processing, often real-time constraints are required. In particular, in safety-critical applications , such as X-ray computed tomography in medical imaging or advanced driver assistance systems in the automotive domain, timing is of utmost importance. A common approach to maintain real-time capabilities of compute-intensive(More)
The development of fast image processing architectures in smart camera systems is a very important task. Nowadays, many applications, such as robot control or advanced driver assistance systems, require fast image acquisition and processing utilizing embedded devices. These requirements have lead to specialized hardware architectures for image processing.(More)
Even with the tremendous performance increase of microprocessor architectures in recent years, real time capturing and computing of stereo images remains a challenging task, particularly in the field of embedded image processing. The stereo block matching technique allows hardware designers to parallelize the process of depth map calculation. Additionally,(More)
The usage of locating systems in sports (e.g. soccer) elevates match and training analysis to a new level. By tracking players and balls during matches or training, the performance of players can be analyzed, the training can be adapted and new strategies can be developed. The radio-based RedFIR system equips players and the ball with miniaturized(More)
Image processing algorithms applied on programmable embedded systems very often do not meet the given constraints in terms of real time capability. Mapping these algorithms to reconfigurable hardware solves this issue, but demands further specific knowledge in hardware development. The design process can be accelerated by code generation through high-level(More)
Recent trends in the image processing field have led to the use of more heterogeneous hardware architectures. The reason for this increase is that specialized cores, compared to standard CPUs, offer a more efficient way of achieving image processing applications. Specialized cores have less power, resource, and area consumption. On the other hand, designing(More)
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