Details
| Original language | English |
|---|---|
| Pages | 125-134 |
| Number of pages | 10 |
| Publication status | Published - 2013 |
Abstract
robust least squares plane fitting improves the results of building extraction especially in case of low accurate point clouds. In addition, region growing in image space has been derived to the fact that grayscale image is more flexible than RGB image and results in more realistic building roofs.
Keywords
- Object surface segmentation, Image segmentation, Region growing, X-Y-Z image, Intensity
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2013. 125-134.
Research output: Contribution to conference › Paper › Research › peer review
}
TY - CONF
T1 - EXTENDED HYBRID REGION GROWING SEGMENTATION OF POINT CLOUDS WITH DIFFERENT RESOLUTION FROM DENSE AERIAL IMAGE MATCHING
AU - Omidalizarandi, Mohammad
AU - Saadatseresht, Mohammad
PY - 2013
Y1 - 2013
N2 - In the recent years, 3D city reconstruction is one of the active researches in the field of photogrammetry. The goal of this work is to improve and extend region growing based segmentation in the X-Y-Z image in the form of 3D structured data with combination of spectral information of RGB and grayscale image to extract building roofs, streets and vegetation. In order to process 3D point clouds, hybrid segmentation is carried out in both object space and image space. Our experiments on two case studies verify that updating plane parameters and robust least squares plane fitting improves the results of building extraction especially in case of low accurate point clouds. In addition, region growing in image space has been derived to the fact that grayscale image is more flexible than RGB image and results in more realistic building roofs.
AB - In the recent years, 3D city reconstruction is one of the active researches in the field of photogrammetry. The goal of this work is to improve and extend region growing based segmentation in the X-Y-Z image in the form of 3D structured data with combination of spectral information of RGB and grayscale image to extract building roofs, streets and vegetation. In order to process 3D point clouds, hybrid segmentation is carried out in both object space and image space. Our experiments on two case studies verify that updating plane parameters and robust least squares plane fitting improves the results of building extraction especially in case of low accurate point clouds. In addition, region growing in image space has been derived to the fact that grayscale image is more flexible than RGB image and results in more realistic building roofs.
KW - Object surface segmentation, Image segmentation, Region growing, X-Y-Z image, Intensity
U2 - 10.5121/csit.2013.3513
DO - 10.5121/csit.2013.3513
M3 - Paper
SP - 125
EP - 134
ER -