Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2018, Cilt: 3 Sayı: 1, 36 - 42, 01.02.2018
https://doi.org/10.26833/ijeg.373152

Öz

Kaynakça

  • Ahmadi, S., Zoej, M. J. V., Ebadi, H., Moghaddam, H. A., Mohammadzadeh, A., 2010, Automatic urban building boundary extraction from high resolution aerial images using an innovative model of active contours, International Journal of Applied Earth Observation and Geoinformation, 12 (2010) 150–157.
  • Alshehhi, R., Marpu, P. R., Woon, W. L., Mura, M. D., 2017, Simultaneous extraction of roads and buildings in remote sensing imagery with convolutional neural networks, ISPRS Journal of Photogrammetry and Remote Sensing, 130 (2017) 139–149.
  • Attarzadeh, R., Momeni, M., 2012, Object-Based Building Extraction from High Resolution Satellite Imagery, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B4, 2012 XXII ISPRS Congress, 25 August – 01 September 2012, Melbourne, Australia.
  • Awrangjeb, M., Fraser, C. S., Lua, G., 2013, Integration of Lidar Data And Orthoimage For Automatic 3D Building Roof Plane Extraction, Multimedia and Expo (ICME), 2013 IEEE International Conference on, doi: 10.1109/ICME.2013.6607612.
  • Chan, T. F. and Vese, L. A., 2001, Active contours without edges, IEEE Transactions on Image Processing, Volume 10, Issue 2, pp. 266-277.
  • Fazan, A. J., Poz, A. P. D., 2013, Rectilinear building roof contour extraction based on snakes and dynamic programming, International Journal of Applied Earth Observation and Geoinformation, doi: 10.1016/j.jag.2013.03.003.
  • Ghaffarian, S., 2015, An Approach For Automatic Building Extraction From High Resolution Satellite Images Using Shadow Analysis And Active Contours Model, Master Thesis, Hacettepe University, Ankara, Turkey.
  • Ghanea, M., Moallem P., Momeni, M., 2014, Automatic Building Extraction in Dense Urban Areas through GeoEye Multi-Spectral Imagery, International Journal of Remote Sensing 35 (13): 5094–5119. doi:10.1080/01431161.2014.933278.
  • Gilani, S. A. N., Awrangjeb, M., Guojun, L., 2016, An Automatic Building Extraction and Regularisation Technique Using LiDAR Point Cloud Data and Orthoimage, Remote Sensing 2016, 8(3), 258, doi: 10.3390/rs8030258.
  • Huang, X., Zhang, L., 2012, Morphological Building/Shadow Index for Building Extraction From High-Resolution Imagery Over Urban Areas, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Volume: 5, Issue: 1, Feb. 2012, doi: 10.1109/JSTARS.2011.2168195.
  • Karsli, F., Dihkan, M., Acar, H., Ozturk, A., 2016, Automatic building extraction from very high-resolution image and LiDAR data with SVM algorithm, Arabian Journal of Geosciences, doi: 10.1007/s12517-016-2664-7.
  • Kass, M., Witkin, A., Terzopoulos, D., 1988, Snakes: Active contour models, International Journal of Computer Vision, 321-331.
  • Kodors, S., Ratkevics, A., Rausis, A., Buls J., 2015, Building Recognition Using LiDAR and Energy Minimization Approach, Procedia Computer Science, Volume 43, 2015, Pages 109-117.
  • Niveetha, M. A., Vidhya, R., 2012, Automatic Building Extraction Using Advanced Morphological Operations and Texture Enhancing, Procedia Engineering 38:3573- 3578.
  • Rutzinger, M, Rottensteiner, F, Pfeifer, N., 2009, A comparison of evaluation techniques for building extraction from airborne laser scanning, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2(1):11–20.
  • Siddiqui, F. U., Teng, S. W., Awrangjeb, M., Lu G., 2016, A Robust Gradient Based Method for Building Extraction from LiDAR and Photogrammetric Imagery, Sensors 2016, 16(7), 1110; doi:10.3390/s16071110.
  • Song, J., Wu, J., Jiang, Y., 2015, Extraction and reconstruction of curved surface buildings by contour clustering using airborne LiDAR data, Optik 126 (2015), 513–521.
  • Shufelt, J. A., 1999, Performance evaluation and analysis of monocular building extraction from aerial imagery. Pattern Analysis and Machine Intelligence, IEEE Transactions on 21(4):311–326.
  • Turker, M., Koc-San, D., 2015, Building extraction from high-resolution optical spaceborne images using the integration of support vector machine (SVM) classification, Hough transformation and perceptual grouping, International Journal of Applied Earth Observation and Geoinformation, 34 (2015) 58–69.
  • URL-1, 2017, https://www.mathworks.com/help/images/re f/activecontour.html, [12 November 2017].
  • Wang, Y., 2016, Automatic Extraction of Building Outline From High Resolution Aerial Imagery, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B3, 2016 XXIII ISPRS Congress, 12–19 July 2016, Prague, Czech Republic.

Automatic extraction of building boundaries from high resolution images with active contour segmentation

Yıl 2018, Cilt: 3 Sayı: 1, 36 - 42, 01.02.2018
https://doi.org/10.26833/ijeg.373152

Öz

Building extraction from remotely sensed images plays an important role in many applications such as updating geographical information system, change detection, urban planning, disaster management and 3D building modeling. Automatic extraction of buildings from aerial images is not an easy task because of background complexity, lighting conditions and vegetation cover that reduces separability or visibility of buildings. As a result, automatic building extraction can be a complex process for computer vision and image processing techniques. In order to overcome this difficulty region-based active contour model was used to automatically detect the boundary of buildings for this study. To extract object boundaries, the model grows or shrinks the initial contour in the image. The main objective of this paper is making active contours algorithm perform without user interaction and to detect automatically initial contours to segment buildings with a software coded in Matlab. This task carried out by morphological operations, band ratio and thresholding methods. In this study, high resolution aerial images with 8 cm ground sampling distance (GSD) were used. Three separate test zones were selected with varying building level of detail on these images. Finally, it was assessed the accuracy of segmented buildings using Correctness, Completeness and Quality metrics by comparing the results images and manually digitized reference image. The proposed approach for building extraction from images was shown to be 98% accurate on buildings with simple geometry and homogeneous roof textures. However accuracy of extracted buildings with heterogeneous roof textures and lighting, and complex geometry is 89%. The results clearly show that automatically calculated initial contour positions work in accordance with the active contour algorithm and easily extraction of the buildings boundaries.

Kaynakça

  • Ahmadi, S., Zoej, M. J. V., Ebadi, H., Moghaddam, H. A., Mohammadzadeh, A., 2010, Automatic urban building boundary extraction from high resolution aerial images using an innovative model of active contours, International Journal of Applied Earth Observation and Geoinformation, 12 (2010) 150–157.
  • Alshehhi, R., Marpu, P. R., Woon, W. L., Mura, M. D., 2017, Simultaneous extraction of roads and buildings in remote sensing imagery with convolutional neural networks, ISPRS Journal of Photogrammetry and Remote Sensing, 130 (2017) 139–149.
  • Attarzadeh, R., Momeni, M., 2012, Object-Based Building Extraction from High Resolution Satellite Imagery, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B4, 2012 XXII ISPRS Congress, 25 August – 01 September 2012, Melbourne, Australia.
  • Awrangjeb, M., Fraser, C. S., Lua, G., 2013, Integration of Lidar Data And Orthoimage For Automatic 3D Building Roof Plane Extraction, Multimedia and Expo (ICME), 2013 IEEE International Conference on, doi: 10.1109/ICME.2013.6607612.
  • Chan, T. F. and Vese, L. A., 2001, Active contours without edges, IEEE Transactions on Image Processing, Volume 10, Issue 2, pp. 266-277.
  • Fazan, A. J., Poz, A. P. D., 2013, Rectilinear building roof contour extraction based on snakes and dynamic programming, International Journal of Applied Earth Observation and Geoinformation, doi: 10.1016/j.jag.2013.03.003.
  • Ghaffarian, S., 2015, An Approach For Automatic Building Extraction From High Resolution Satellite Images Using Shadow Analysis And Active Contours Model, Master Thesis, Hacettepe University, Ankara, Turkey.
  • Ghanea, M., Moallem P., Momeni, M., 2014, Automatic Building Extraction in Dense Urban Areas through GeoEye Multi-Spectral Imagery, International Journal of Remote Sensing 35 (13): 5094–5119. doi:10.1080/01431161.2014.933278.
  • Gilani, S. A. N., Awrangjeb, M., Guojun, L., 2016, An Automatic Building Extraction and Regularisation Technique Using LiDAR Point Cloud Data and Orthoimage, Remote Sensing 2016, 8(3), 258, doi: 10.3390/rs8030258.
  • Huang, X., Zhang, L., 2012, Morphological Building/Shadow Index for Building Extraction From High-Resolution Imagery Over Urban Areas, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Volume: 5, Issue: 1, Feb. 2012, doi: 10.1109/JSTARS.2011.2168195.
  • Karsli, F., Dihkan, M., Acar, H., Ozturk, A., 2016, Automatic building extraction from very high-resolution image and LiDAR data with SVM algorithm, Arabian Journal of Geosciences, doi: 10.1007/s12517-016-2664-7.
  • Kass, M., Witkin, A., Terzopoulos, D., 1988, Snakes: Active contour models, International Journal of Computer Vision, 321-331.
  • Kodors, S., Ratkevics, A., Rausis, A., Buls J., 2015, Building Recognition Using LiDAR and Energy Minimization Approach, Procedia Computer Science, Volume 43, 2015, Pages 109-117.
  • Niveetha, M. A., Vidhya, R., 2012, Automatic Building Extraction Using Advanced Morphological Operations and Texture Enhancing, Procedia Engineering 38:3573- 3578.
  • Rutzinger, M, Rottensteiner, F, Pfeifer, N., 2009, A comparison of evaluation techniques for building extraction from airborne laser scanning, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2(1):11–20.
  • Siddiqui, F. U., Teng, S. W., Awrangjeb, M., Lu G., 2016, A Robust Gradient Based Method for Building Extraction from LiDAR and Photogrammetric Imagery, Sensors 2016, 16(7), 1110; doi:10.3390/s16071110.
  • Song, J., Wu, J., Jiang, Y., 2015, Extraction and reconstruction of curved surface buildings by contour clustering using airborne LiDAR data, Optik 126 (2015), 513–521.
  • Shufelt, J. A., 1999, Performance evaluation and analysis of monocular building extraction from aerial imagery. Pattern Analysis and Machine Intelligence, IEEE Transactions on 21(4):311–326.
  • Turker, M., Koc-San, D., 2015, Building extraction from high-resolution optical spaceborne images using the integration of support vector machine (SVM) classification, Hough transformation and perceptual grouping, International Journal of Applied Earth Observation and Geoinformation, 34 (2015) 58–69.
  • URL-1, 2017, https://www.mathworks.com/help/images/re f/activecontour.html, [12 November 2017].
  • Wang, Y., 2016, Automatic Extraction of Building Outline From High Resolution Aerial Imagery, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B3, 2016 XXIII ISPRS Congress, 12–19 July 2016, Prague, Czech Republic.
Toplam 21 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Articles
Yazarlar

Zeynep Akbulut 0000-0001-9801-1506

Samed Özdemir 0000-0001-7217-899X

Hayrettin Acar 0000-0002-2954-7734

Mustafa Dihkan 0000-0002-0027-236X

Fevzi Karslı 0000-0002-0411-3315

Yayımlanma Tarihi 1 Şubat 2018
Yayımlandığı Sayı Yıl 2018 Cilt: 3 Sayı: 1

Kaynak Göster

APA Akbulut, Z., Özdemir, S., Acar, H., Dihkan, M., vd. (2018). Automatic extraction of building boundaries from high resolution images with active contour segmentation. International Journal of Engineering and Geosciences, 3(1), 36-42. https://doi.org/10.26833/ijeg.373152
AMA Akbulut Z, Özdemir S, Acar H, Dihkan M, Karslı F. Automatic extraction of building boundaries from high resolution images with active contour segmentation. IJEG. Şubat 2018;3(1):36-42. doi:10.26833/ijeg.373152
Chicago Akbulut, Zeynep, Samed Özdemir, Hayrettin Acar, Mustafa Dihkan, ve Fevzi Karslı. “Automatic Extraction of Building Boundaries from High Resolution Images With Active Contour Segmentation”. International Journal of Engineering and Geosciences 3, sy. 1 (Şubat 2018): 36-42. https://doi.org/10.26833/ijeg.373152.
EndNote Akbulut Z, Özdemir S, Acar H, Dihkan M, Karslı F (01 Şubat 2018) Automatic extraction of building boundaries from high resolution images with active contour segmentation. International Journal of Engineering and Geosciences 3 1 36–42.
IEEE Z. Akbulut, S. Özdemir, H. Acar, M. Dihkan, ve F. Karslı, “Automatic extraction of building boundaries from high resolution images with active contour segmentation”, IJEG, c. 3, sy. 1, ss. 36–42, 2018, doi: 10.26833/ijeg.373152.
ISNAD Akbulut, Zeynep vd. “Automatic Extraction of Building Boundaries from High Resolution Images With Active Contour Segmentation”. International Journal of Engineering and Geosciences 3/1 (Şubat 2018), 36-42. https://doi.org/10.26833/ijeg.373152.
JAMA Akbulut Z, Özdemir S, Acar H, Dihkan M, Karslı F. Automatic extraction of building boundaries from high resolution images with active contour segmentation. IJEG. 2018;3:36–42.
MLA Akbulut, Zeynep vd. “Automatic Extraction of Building Boundaries from High Resolution Images With Active Contour Segmentation”. International Journal of Engineering and Geosciences, c. 3, sy. 1, 2018, ss. 36-42, doi:10.26833/ijeg.373152.
Vancouver Akbulut Z, Özdemir S, Acar H, Dihkan M, Karslı F. Automatic extraction of building boundaries from high resolution images with active contour segmentation. IJEG. 2018;3(1):36-42.

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