SEGMENTATION AND CLASSIFICATION OF POINT CLOUDS FROM DENSE AERIAL IMAGE MATCHING

Research output: Contribution to journalArticleResearchpeer review

Authors

Research Organisations

External Research Organisations

  • University of Tehran
View graph of relations

Details

Original languageEnglish
Number of pages33
JournalThe International Journal of Multimedia & Its Applications (IJMA)
Volume5
Issue number4
Publication statusPublished - 1 Aug 2013

Abstract

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 surface growing based segmentation in the XYZ 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 three 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.

Keywords

    Object Surface Segmentation, Image Segmentation, Classification, Region Growing, X-Y-Z Image, Intensity

Cite this

SEGMENTATION AND CLASSIFICATION OF POINT CLOUDS FROM DENSE AERIAL IMAGE MATCHING. / Omidalizarandi, Mohammad; Saadatseresht, Mohammad .
In: The International Journal of Multimedia & Its Applications (IJMA) , Vol. 5, No. 4, 01.08.2013.

Research output: Contribution to journalArticleResearchpeer review

Omidalizarandi, M & Saadatseresht, M 2013, 'SEGMENTATION AND CLASSIFICATION OF POINT CLOUDS FROM DENSE AERIAL IMAGE MATCHING', The International Journal of Multimedia & Its Applications (IJMA) , vol. 5, no. 4. https://doi.org/10.5121/ijma.2013.5403
Omidalizarandi, M., & Saadatseresht, M. (2013). SEGMENTATION AND CLASSIFICATION OF POINT CLOUDS FROM DENSE AERIAL IMAGE MATCHING. The International Journal of Multimedia & Its Applications (IJMA) , 5(4). https://doi.org/10.5121/ijma.2013.5403
Omidalizarandi M, Saadatseresht M. SEGMENTATION AND CLASSIFICATION OF POINT CLOUDS FROM DENSE AERIAL IMAGE MATCHING. The International Journal of Multimedia & Its Applications (IJMA) . 2013 Aug 1;5(4). doi: 10.5121/ijma.2013.5403
Omidalizarandi, Mohammad ; Saadatseresht, Mohammad . / SEGMENTATION AND CLASSIFICATION OF POINT CLOUDS FROM DENSE AERIAL IMAGE MATCHING. In: The International Journal of Multimedia & Its Applications (IJMA) . 2013 ; Vol. 5, No. 4.
Download
@article{27b7f8b668e748b79834b97626c1b218,
title = "SEGMENTATION AND CLASSIFICATION OF POINT CLOUDS FROM DENSE AERIAL IMAGE MATCHING",
abstract = "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 surface growing based segmentation in the XYZ 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 three 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.",
keywords = "Object Surface Segmentation, Image Segmentation, Classification, Region Growing, X-Y-Z Image, Intensity",
author = "Mohammad Omidalizarandi and Mohammad Saadatseresht",
year = "2013",
month = aug,
day = "1",
doi = "10.5121/ijma.2013.5403",
language = "English",
volume = "5",
number = "4",

}

Download

TY - JOUR

T1 - SEGMENTATION AND CLASSIFICATION OF POINT CLOUDS FROM DENSE AERIAL IMAGE MATCHING

AU - Omidalizarandi, Mohammad

AU - Saadatseresht, Mohammad

PY - 2013/8/1

Y1 - 2013/8/1

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 surface growing based segmentation in the XYZ 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 three 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 surface growing based segmentation in the XYZ 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 three 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, Classification, Region Growing, X-Y-Z Image, Intensity

U2 - 10.5121/ijma.2013.5403

DO - 10.5121/ijma.2013.5403

M3 - Article

VL - 5

JO - The International Journal of Multimedia & Its Applications (IJMA)

JF - The International Journal of Multimedia & Its Applications (IJMA)

IS - 4

ER -

By the same author(s)