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2021 | OriginalPaper | Buchkapitel

Image Segmentation of Bricks in Masonry Wall Using a Fusion of Machine Learning Algorithms

verfasst von : Roland Kajatin, Lazaros Nalpantidis

Erschienen in: Pattern Recognition. ICPR International Workshops and Challenges

Verlag: Springer International Publishing

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Abstract

Autonomous mortar raking requires a computer vision system which is able to provide accurate segmentation masks of close-range images of brick walls. The goal is to detect and ultimately remove the mortar, leaving the bricks intact, thus automating this construction-related task. This paper proposes such a vision system based on the combination of machine learning algorithms. The proposed system fuses the individual segmentation outputs of eight classifiers by means of a weighted voting scheme and then performing a threshold operation to generate the final binary segmentation. A novel feature of this approach is the fusion of several segmentations using a low-cost commercial off-the-shelf hardware setup. The close-range brick wall segmentation capabilities of the system are demonstrated on a total of about 9 million data points.

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Titel: Image Segmentation of Bricks in Masonry Wall Using a Fusion of Machine Learning Algorithms
verfasst von: Roland Kajatin
Lazaros Nalpantidis
Verlag: Springer International Publishing
Buch: Pattern Recognition. ICPR International Workshops and Challenges
Print ISBN: 978-3-030-68786-1

Electronic ISBN: 978-3-030-68787-8

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-3-030-68787-8_33

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