Automatic extraction of building boundaries from high resolution images with active contour segmentation
Abstract
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.
Keywords
References
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Details
Primary Language
English
Subjects
-
Journal Section
Research Article
Authors
Zeynep Akbulut
*
GÜMÜŞHANE ÜNİVERSİTESİ
0000-0001-9801-1506
Türkiye
Samed Özdemir
GÜMÜŞHANE ÜNİVERSİTESİ
0000-0001-7217-899X
Türkiye
Hayrettin Acar
KARADENİZ TEKNİK ÜNİVERSİTESİ
0000-0002-2954-7734
Türkiye
Mustafa Dihkan
KARADENİZ TEKNİK ÜNİVERSİTESİ
0000-0002-0027-236X
Türkiye
Fevzi Karslı
KARADENİZ TEKNİK ÜNİVERSİTESİ
0000-0002-0411-3315
Türkiye
Publication Date
February 1, 2018
Submission Date
December 30, 2017
Acceptance Date
January 23, 2018
Published in Issue
Year 2018 Volume: 3 Number: 1
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