University of Twente Student Theses


Digital billboard damage detection using computer vision

Boersen, N. (2019) Digital billboard damage detection using computer vision.

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Abstract:Digital billboards for marketing purposes are nowadays commons sight along the Dutch highways. A company that sells, constructs and does the maintenance of these outdoor LED screens is Hecla Professional. Like all electrical devices, these billboards are susceptible to breakage. This paper focusses on the development of a system that detects broken LED tiles in billboards by artificially checking video streams. The system also informs the technical staff when it detects a malfunctioning LED tile. The prototyped system does this by using state-of-the-art deep-learning object detection methods. In this study, an accuracy of 83.79% was achieved on an experimental setup. These experimental results from an indoor setup demonstrate that the proposed prototype can, in fact, detect the defective LED tiles and that the system can be used for this job.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science, 58 process technology
Programme:Creative Technology BSc (50447)
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