TY - GEN
T1 - Evaluation of Segmentation Methods for Spoil Pile Delineation Using UAV Images
AU - Thiruchittampalam, S.
AU - Banerjee, B. P.
AU - Singh, S. K.
AU - Glenn, N. F.
AU - Raval, S.
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Mine dump stability depends on the correct placement of fundamental units - i.e., spoil piles, based on their geological and geotechnical characteristics. In-field characterization of individual piles is strenuous. To this end, image-based characterization of spoil piles using remote data obtained through unpiloted aerial system is a potential complementary solution. Several high-level image processing techniques such as object-based classification and feature extraction, inherently rely on effective segmentation. However, studies on segmentation algorithms for spoil pile delineation are lacking. This study provides insight on colour-based and morphology-based segmentation approaches to progress avenues for object-based analysis for spoil characterization in the mine environment.
AB - Mine dump stability depends on the correct placement of fundamental units - i.e., spoil piles, based on their geological and geotechnical characteristics. In-field characterization of individual piles is strenuous. To this end, image-based characterization of spoil piles using remote data obtained through unpiloted aerial system is a potential complementary solution. Several high-level image processing techniques such as object-based classification and feature extraction, inherently rely on effective segmentation. However, studies on segmentation algorithms for spoil pile delineation are lacking. This study provides insight on colour-based and morphology-based segmentation approaches to progress avenues for object-based analysis for spoil characterization in the mine environment.
KW - Mean-shift segmentation
KW - Mine dumps
KW - Simple linear iterative clustering
KW - Spoil piles
KW - Voronoi-based segmentation
UR - https://www.scopus.com/pages/publications/85171411550
U2 - 10.1109/IGARSS52108.2023.10283351
DO - 10.1109/IGARSS52108.2023.10283351
M3 - Conference contribution
AN - SCOPUS:85171411550
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 2450
EP - 2453
BT - IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023
Y2 - 16 July 2023 through 21 July 2023
ER -