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dc.contributor.authorShishido, H.
dc.contributor.authorWanzhi, Z.
dc.contributor.authorJang, Hyong Doo
dc.contributor.authorKawamura, Y.
dc.contributor.authorKameda, Y.
dc.contributor.authorKitahara, I.
dc.identifier.citationShishido, H. and Wanzhi, Z. and Jang, H.D. and Kawamura, Y. and Kameda, Y. and Kitahara, I. 2019. Clustering Method of 3D Point Cloud of Muck-Pile Based on Connectivity of Adjacent Surface. In: 2019 IEEE 8th Global Conference on Consumer Electronics (GCCE 2019), 15th Oct 2019, OSAKA, Japan.

This paper proposes a method to measure the fragmentation distribution of a pile of rocks (muck-pile) using image-based 3D reconstruction. One of the most important aspects of mine-blasting is appropriate rock fragmentation to optimize the cost of the blasting operation. The conventional method of measuring fragmentation distribution is based on 2D image processing including segmentation of muck-pile regions into rock clusters. However, in the 2D method, the measurement accuracy is limited. To accurately measure rock fragmentation distribution, we reconstructed a 3D model of a muck-pile from multi-view images and segment the 3D model based on rock-features such as color, normal vector, distance and adjacent angles of surface planes. As a result, the size of each rock was calculated by fitting a bounding box. Based on experimental evaluations, it was confirmed that the accuracy of the proposed method is higher than that of previous methods.

dc.subject0914 - Resources Engineering and Extractive Metallurgy
dc.titleClustering Method of 3D Point Cloud of Muck-Pile Based on Connectivity of Adjacent Surface
dc.typeConference Paper
dcterms.source.conference2019 IEEE 8th Global Conference on Consumer Electronics (GCCE 2019)
dcterms.source.conference-start-date15 Oct 2019
dcterms.source.conferencelocationOSAKA, Japan
curtin.departmentWASM: Minerals, Energy and Chemical Engineering
curtin.accessStatusOpen access
curtin.facultyFaculty of Science and Engineering
curtin.contributor.orcidJang, Hyong Doo [0000-0002-3978-5840]
curtin.contributor.orcidJang, Hyong Doo [0000-0002-3978-5840]
dcterms.source.conference-end-date18 Oct 2019
curtin.contributor.scopusauthoridJang, Hyong Doo [55797412200]
curtin.contributor.scopusauthoridJang, Hyong Doo [55797412200]

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