Akademik Veri Yönetim Sistemi
Tezin Türü: Yüksek Lisans
Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü, Türkiye
Tezin Onay Tarihi: 2008
Öğrenci: ABDURRAHMAN YALÇIN
Danışman: UĞUR HALICI
Özet:Rectangular-shaped building detection from high resolution aerial/satellite images is proposed for two different methods. Shadow information plays main role in both of these algorithms. One of the algorithms is based on Hough transformation, the other one is based on mean shift segmentation algorithm. Satellite/aerial images are firstly converted to YIQ color space to be used in shadow segmentation. Hue and intensity values are used in computing the ratio image which is used to segment shadowed regions. For shadow segmentation Otsu’s method is used on the histogram of the ratio image. The segmented shadow image is used as the input for both of two building detection algorithms. In the proposed methods, shadowed regions are believed to be the building shadows. So, non-shadowed regions such as roads, cars, trees etc. are discarded before processing the image. In Hough transform based building detection algorithm, shadowed regions are firstly segmented one by one and filtered for noise removal and edge sharpening. Then, the edges in the filtered image are detected by using Canny edge detection algorithm. Then, line segments are extracted. Finally, the extracted line segments are used to construct rectangular-shaped buildings. In mean shift based building detection algorithm, image is firstly segmented by using mean shift segmentation algorithm. By using shadow image and segmented image, building rooftops are investigated in shadow boundaries. The results are compared for both of the algorithms. In the last step a shadow removal algorithm is implemented to observe the effects of shadow regions in both of two implemented building detection algorithms. Both of these algorithms are applied to shadow removed image and results are compared.