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
Tezin Dili: İngilizce
Öğrenci: Mustafa Yavuz Kırlı
Danışman: İLKAY ULUSOY
Özet:The aim of this thesis is to reconstruct 3D representation of underwater scenes from uncalibrated video sequences. Underwater visualization is important for underwater Remotely Operated Vehicles and underwater is a complex structured environment because of inhomogeneous light absorption and light scattering by the environment. These factors make 3D reconstruction in underwater more challenging. The reconstruction consists of the following stages: Image enhancement, feature detection and matching, fundamental matrix estimation, auto-calibration, recovery of extrinsic parameters, rectification, stereo matching and triangulation. For image enhancement, a pre-processing filter is used to remove the effects of water and to enhance the images. Two feature extraction methods are examined: 1. Difference of Gaussian with SIFT feature descriptor, 2. Harris Corner Detector with grey level around the feature point. Matching is performed by finding similarities of SIFT features and by finding correlated grey levels respectively for each feature extraction method. The results show that SIFT performs better than Harris with grey level information. RANSAC method with normalized 8-point algorithm is used to estimate fundamental matrix and to reject outliers. Because of the difficulties of calibrating the cameras in underwater, auto-calibration process is examined. Rectification is also performed since it provides epipolar lines coincide with image scan lines which is helpful to stereo matching algorithms. The Graph-Cut stereo matching algorithm is used to compute corresponding pixel of each pixel in the stereo image pair. For the last stage triangulation is used to compute 3D points from the corresponding pixel pairs.