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A gabor filter-based protocol for automated image-based building detection

Munawar, Hafiz Suliman, Aggarwal, Riya, Qadir, Zakria, Khan, Sara Imran, Kouzani, Abbas Z. and Mahmud, M A Parvez 2021, A gabor filter-based protocol for automated image-based building detection, Buildings, vol. 11, no. 7, pp. 1-15, doi: 10.3390/buildings11070302.

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Title A gabor filter-based protocol for automated image-based building detection
Author(s) Munawar, Hafiz Suliman
Aggarwal, Riya
Qadir, Zakria
Khan, Sara Imran
Kouzani, Abbas Z.ORCID iD for Kouzani, Abbas Z. orcid.org/0000-0002-6292-1214
Mahmud, M A ParvezORCID iD for Mahmud, M A Parvez orcid.org/0000-0002-1905-6800
Journal name Buildings
Volume number 11
Issue number 7
Article ID 302
Start page 1
End page 15
Total pages 15
Publisher MDPI AG
Publication date 2021
ISSN 2075-5309
Summary Detecting buildings from high-resolution satellite imagery is beneficial in mapping, environmental preparation, disaster management, military planning, urban planning and research purposes. Differentiating buildings from the images is possible however, it may be a time-consuming or complicated process. Therefore, the high-resolution imagery from satellites needs to be automated to detect the buildings. Additionally, buildings exhibit several different characteristics, and their appearance in these images is unplanned. Moreover, buildings in the metropolitan environment are typically crowded and complicated. Therefore, it is challenging to identify the building and hard to locate them. To resolve this situation, a novel probabilistic method has been suggested using local features and probabilistic approaches. A local feature extraction technique was implemented, which was used to calculate the probability density function. The locations in the image were represented as joint probability distributions and were used to estimate their probability distribution function (pdf). The density of building locations in the image was extracted. Kernel density distribution was also used to find the density flow for different metropolitan cities such as Sydney (Australia), Tokyo (Japan), and Mumbai (India), which is useful for distribution intensity and pattern of facility point f interest (POI). The purpose system can detect buildings/rooftops and to test our system, we choose some crops with panchromatic high-resolution satellite images from Australia and our results looks promising with high efficiency and minimal computational time for feature extraction. We were able to detect buildings with shadows and building without shadows in 0.4468 (seconds) and 0.5126 (seconds) respectively.
DOI 10.3390/buildings11070302
Indigenous content off
Field of Research 1201 Architecture
1202 Building
1203 Design Practice and Management
HERDC Research category C1 Refereed article in a scholarly journal
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30153686

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.