• Media type: Text; Doctoral Thesis; Electronic Thesis; E-Book
  • Title: Exploration of cyber-physical systems for GPGPU computer vision-based detection of biological viruses
  • Contributor: Libuschewski, Pascal [Author]
  • Published: Eldorado - Repositorium der TU Dortmund, 2017-01-01
  • Language: English
  • DOI: https://doi.org/10.17877/DE290R-17952
  • Keywords: Design space exploration ; Biological viruses ; Computer vision ; Optimization ; Medical image processing ; GPGPU ; Embedded systems ; Energy-aware ; Mobile sensor ; Virus detection ; GPU ; Multi-objective ; Cyber-physical systems ; DSE
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  • Description: This work presents a method for a computer vision-based detection of biological viruses in PAMONO sensor images and, related to this, methods to explore cyber-physical systems such as those consisting of the PAMONO sensor, the detection software, and processing hardware. The focus is especially on an exploration of Graphics Processing Units (GPU) hardware for “General-Purpose computing on Graphics Processing Units” (GPGPU) software and the targeted systems are high performance servers, desktop systems, mobile systems, and hand-held systems. The first problem that is addressed and solved in this work is to automatically detect biological viruses in PAMONO sensor images. PAMONO is short for “Plasmon Assisted Microscopy Of Nano-sized Objects”. The images from the PAMONO sensor are very challenging to process. The signal magnitude and spatial extension from attaching viruses is small, and it is not visible to the human eye on raw sensor images. Compared to the signal, the noise magnitude in the images is large, resulting in a small Signal-to-Noise Ratio (SNR). With the VirusDetectionCL method for a computer vision-based detection of viruses, presented in this work, an automatic detection and counting of individual viruses in PAMONO sensor images has been made possible. A data set of 4000 images can be evaluated in less than three minutes, whereas a manual evaluation by an expert can take up to two days. As the most important result, sensor signals with a median SNR of two can be handled. This enables the detection of particles down to 100 nm. The VirusDetectionCL method has been realized as a GPGPU software. The PAMONO sensor, the detection software, and the processing hardware form a so called cyber-physical system. For different PAMONO scenarios, e.g., using the PAMONO sensor in laboratories, hospitals, airports, and in mobile scenarios, one or more cyber-physical systems need to be explored. Depending on the particular use case, the demands toward the cyber-physical system differ. This leads to the second problem ...
  • Access State: Open Access
  • Rights information: In Copyright