Range image segmentation for tree detection in forest scans

To make a tree-wise analysis inside a forest stand, the trees have to be identified. An interactive segmentation is often labourintensive and time-consuming. Therefore, an automatic detection process will aspired using a range image. This paper presents a method for the segmentation of range image...

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Main Authors: A. Bienert, D. Schneider
Format: Article
Language:English
Published: Copernicus Publications 2013-10-01
Series:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-5-W2/49/2013/isprsannals-II-5-W2-49-2013.pdf
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author A. Bienert
D. Schneider
author_facet A. Bienert
D. Schneider
author_sort A. Bienert
collection DOAJ
description To make a tree-wise analysis inside a forest stand, the trees have to be identified. An interactive segmentation is often labourintensive and time-consuming. Therefore, an automatic detection process will aspired using a range image. This paper presents a method for the segmentation of range images extracted from terrestrial laser scanner point clouds of forest stands. After range image generation the segmentation is carried out with a connectivity analysis using the differences of the range values as homogeneity criterion. Subsequently, the tree detection is performed interactively by analysing one horizontal image line. When passing objects with a specific width, the object indicates a potential tree. By using the edge points of a segmented pixel group the tree position and diameter is calculated. Results from one test site are presented to show the performance of the method.
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spelling doaj.art-296cb4d97a0a42fcac40c6f7504afc832022-12-21T18:44:41ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502013-10-01II-5-W2495410.5194/isprsannals-II-5-W2-49-2013Range image segmentation for tree detection in forest scansA. Bienert0D. Schneider1Technische Universität Dresden, Institute of Photogrammetry and Remote Sensing, 01062 Dresden, GermanyTechnische Universität Dresden, Institute of Photogrammetry and Remote Sensing, 01062 Dresden, GermanyTo make a tree-wise analysis inside a forest stand, the trees have to be identified. An interactive segmentation is often labourintensive and time-consuming. Therefore, an automatic detection process will aspired using a range image. This paper presents a method for the segmentation of range images extracted from terrestrial laser scanner point clouds of forest stands. After range image generation the segmentation is carried out with a connectivity analysis using the differences of the range values as homogeneity criterion. Subsequently, the tree detection is performed interactively by analysing one horizontal image line. When passing objects with a specific width, the object indicates a potential tree. By using the edge points of a segmented pixel group the tree position and diameter is calculated. Results from one test site are presented to show the performance of the method.https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-5-W2/49/2013/isprsannals-II-5-W2-49-2013.pdf
spellingShingle A. Bienert
D. Schneider
Range image segmentation for tree detection in forest scans
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title Range image segmentation for tree detection in forest scans
title_full Range image segmentation for tree detection in forest scans
title_fullStr Range image segmentation for tree detection in forest scans
title_full_unstemmed Range image segmentation for tree detection in forest scans
title_short Range image segmentation for tree detection in forest scans
title_sort range image segmentation for tree detection in forest scans
url https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-5-W2/49/2013/isprsannals-II-5-W2-49-2013.pdf
work_keys_str_mv AT abienert rangeimagesegmentationfortreedetectioninforestscans
AT dschneider rangeimagesegmentationfortreedetectioninforestscans