dc.contributor.author | Stirbys, Justinas | |
dc.date.accessioned | 2019-11-18T15:28:33Z | |
dc.date.available | 2019-11-18T15:28:33Z | |
dc.date.issued | 2019-11-18 | |
dc.identifier.uri | http://hdl.handle.net/2077/62547 | |
dc.description.abstract | The purpose of this paper is to provide a highspeed
image capturing and cone detection algorithm using lowcost
devices, such as a Raspberry Pi and Pi NoIR V2 camera
module. Little research focuses on high-speed, low-cost image
processing. Most existing literature aimed at achieving a high
FPS, use expensive tools, such as LiDARs or high-speed cameras.
Thus creating a gap in knowledge. Design science was used
to develop and evaluate our artifact. For evaluation, controlled
experiments were used to gather data. The collected data shows
that our artifact is able to capture and detect cones at 30-35FPS
with varying, 42-83%, cone detection rate and cone detection
accuracy ranging from 9% to 69%. The results show that lowcost,
real-time image capture and processing are achievable. The
study could be used to provide a cost effective solution for cone
detection. Additionally, the solution’s low-cost provides more
opportunities to develop and innovate in this area. | sv |
dc.language.iso | eng | sv |
dc.title | High-speed Image Capture and Cone Detection Using a Raspberry Pi and Camera Module: A Design Science Approach | sv |
dc.type | text | |
dc.setspec.uppsok | Technology | |
dc.type.uppsok | M2 | |
dc.contributor.department | Göteborgs universitet/Institutionen för data- och informationsteknik | swe |
dc.contributor.department | University of Gothenburg/Department of Computer Science and Engineering | eng |
dc.type.degree | Student essay | |