Pathfinder’s Tech X DSTA challenge - elevator control vision module : elevator button detection & activation

This report presents a computer vision system use to identify and press targeted button(s) on an elevator control panel based upon contour detection. In additional, there is no prior knowledge about the size, shape, colour, texture and images of the targeted button(s). But strong specular reflectio...

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Main Author: Lum, Jackson Guan Ting.
Other Authors: Goh Wooi Boon
Format: Final Year Project
Language:English
Published: 2009
Subjects:
Online Access:http://hdl.handle.net/10356/18984
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-189842023-03-03T20:25:30Z Pathfinder’s Tech X DSTA challenge - elevator control vision module : elevator button detection & activation Lum, Jackson Guan Ting. Goh Wooi Boon School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision This report presents a computer vision system use to identify and press targeted button(s) on an elevator control panel based upon contour detection. In additional, there is no prior knowledge about the size, shape, colour, texture and images of the targeted button(s). But strong specular reflections present on the polished surfaces of the button(s) hamper reliability and performance of the contour detection. To overcome this, techniques such as Hough transform, morphological Closing and utilising information from preceding frames were experimented upon. Geometric relationship between detected buttons are then used to infer their respectively storey levels which they represent. A novel technique called Geometric Relationship Button Clustering level for clustering grid-like pattern of the buttons was implemented and discussed. Test shows that the system can successfully detect up to 82.66% of the actual buttons with 1.52% false positives. At an execution time of 200.413 ms per frame. More notably, the system is able to tolerate control panels that are not perfectly upright and/or some degree of perspective distortion. Bachelor of Engineering (Computer Engineering) 2009-08-26T07:52:59Z 2009-08-26T07:52:59Z 2009 2009 Final Year Project (FYP) http://hdl.handle.net/10356/18984 en Nanyang Technological University 93 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Lum, Jackson Guan Ting.
Pathfinder’s Tech X DSTA challenge - elevator control vision module : elevator button detection & activation
description This report presents a computer vision system use to identify and press targeted button(s) on an elevator control panel based upon contour detection. In additional, there is no prior knowledge about the size, shape, colour, texture and images of the targeted button(s). But strong specular reflections present on the polished surfaces of the button(s) hamper reliability and performance of the contour detection. To overcome this, techniques such as Hough transform, morphological Closing and utilising information from preceding frames were experimented upon. Geometric relationship between detected buttons are then used to infer their respectively storey levels which they represent. A novel technique called Geometric Relationship Button Clustering level for clustering grid-like pattern of the buttons was implemented and discussed. Test shows that the system can successfully detect up to 82.66% of the actual buttons with 1.52% false positives. At an execution time of 200.413 ms per frame. More notably, the system is able to tolerate control panels that are not perfectly upright and/or some degree of perspective distortion.
author2 Goh Wooi Boon
author_facet Goh Wooi Boon
Lum, Jackson Guan Ting.
format Final Year Project
author Lum, Jackson Guan Ting.
author_sort Lum, Jackson Guan Ting.
title Pathfinder’s Tech X DSTA challenge - elevator control vision module : elevator button detection & activation
title_short Pathfinder’s Tech X DSTA challenge - elevator control vision module : elevator button detection & activation
title_full Pathfinder’s Tech X DSTA challenge - elevator control vision module : elevator button detection & activation
title_fullStr Pathfinder’s Tech X DSTA challenge - elevator control vision module : elevator button detection & activation
title_full_unstemmed Pathfinder’s Tech X DSTA challenge - elevator control vision module : elevator button detection & activation
title_sort pathfinder’s tech x dsta challenge - elevator control vision module : elevator button detection & activation
publishDate 2009
url http://hdl.handle.net/10356/18984
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