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Real time embedded system for holes detection in fish farming nets

Badogiannis Nikolaos

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URI: http://purl.tuc.gr/dl/dias/AD2CBAC0-71D0-4E6A-841C-72E9C64B4671
Year 2019
Type of Item Diploma Work
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Bibliographic Citation Nikolaos Badogiannis, "Real time embedded system for holes detection in fish farming nets", Diploma Work, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2019 https://doi.org/10.26233/heallink.tuc.83273
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Summary

Image processing techniques are used by the industry for the quality control ofthe products. Their complexity demands research on methods that can accelerate these techniques on hardware and make possible their use on real time embedded systems with low power consumption.This thesis diploma studies image processing methods for the detection of holes on fish farming nets. The main purpose of this thesis is to design a real time embedded system with low execution time and power consumption. Once implemented algorithms that use Template Matching and Edge Detection techniques, we studied them experimentally using Matlab to detect if they can be used for this purpose. Then we implemented our algorithms on FPGA and checked their demands on resources, power consumption and total execution time.

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