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:: Volume 9, Issue 2 (summer 2018) ::
3 2018, 9(2): 231-242 Back to browse issues page
Improvement of Buildings Detection Based on Adaptive Thresholding in Satellite Images
Abstract:   (653 Views)
In this paper, a combined method to detect buildings from satellite imagery is presented. This method is based on combining data obtained by the local feature vectors and decision-making by applying adaptive thresholding the estimated probability distribution function, is conducted. Local Features serve as observations and location of buildings are used as joint random variables in order to estimate the probability density function. Then the locations of buildings are determined by considering modes of estimated probability density function and extracted features. To evaluate the efficiency of proposed method some satellite imagery of northern Tehran is used. Satellites North of Tehran building images are used in order to evaluate our proposed method. Tested images have different spatial contrast and resolution. Furthermore, tested buildings contain variety of characteristics which allows us representing our simulation with sufficient diversity. Experimental results of 32 different images in Tehran have shown that proposed method can be detected existing buildings in satellite imagery with fewer errors and more accurately.
Keywords: satellite images, Building Detection, feature extraction, probability density function, random variables
Full-Text [PDF 1386 kb]   (322 Downloads)    
Type of Study: Applicable | Subject: computer
Received: 2017/01/1 | Accepted: 2017/12/25 | Published: 2018/03/3
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Improvement of Buildings Detection Based on Adaptive Thresholding in Satellite Images. 3. 2018; 9 (2) :231-242
URL: http://adst.ir/article-1-991-en.html

Volume 9, Issue 2 (summer 2018) Back to browse issues page
علوم و فناوری های پدافند نوین ADST Journal
درجه علمی - پژوهشی توسط وزارت علوم، تحقیقات و فناوری اعطا گردید.