Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/11
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Conference Object Matching Aerial Coastline Images With Map Data Using Dynamic Programming(Institute of Electrical and Electronics Engineers Inc., 2006) Kahraman, Metin; Gümüştekin, ŞevketMatching aerial images with map data is an important task in several remote sensing applications such as autonomous navigation, cartography, oceanography. The unique and distinctive shapes of coastlines can be effectively utilized to solve this problem. In this study a completely automatic scheme is proposed to detect coastlines using multiresolution texture analysis and to match the detected coastlines to a map database. A shape matching method using dynamic programming is used and tested on the satellite images of the western coast of Turkey.Article Citation - WoS: 2Citation - Scopus: 2Enhancing Stereo Matching Performance by Colour Normalisation and Specularity Removal(Institution of Engineering and Technology, 2011) Ozan, Şükrü; Gümüştekin, ŞevketA method to enhance the performance of stereo matching is presented. The position of the specular light reflection on an object surface varies due to the change in the position of the camera, light source, object or all combined. Additionally, there may be situations exhibiting a colour shift owing to a change in the light source chromaticity or camera white balance settings. These variations cause misleading results when stereo matching algorithms are applied. In this reported work, a single-image-based statistical method is used to normalise source images. This process effectively eliminates non-saturated specularities regardless of their positions on the object. The effect of specularity removal is tested on stereo image pairs. © 2011 The Institution of Engineering and Technology.Conference Object Citation - WoS: 1Citation - Scopus: 2A Case Study on Logging Visual Activities: Chess Game(Springer Verlag, 2006) Ozan, Şükrü; Gümüştekin, ŞevketAutomatically recognizing and analyzing visual activities in complex environments is a challenging and open-ended problem. In this study this task is performed in a chess game scenario where the rules, actions and the environment are well defined. The purpose here is to detect and observe a FIDE (Fédération International des Ėchecs) compatible chess board, generating a log file of the moves made by human players. A series of basic image processing operations have been applied to perform the desired task. The first step of automatically detecting a chess board is followed by locating the positions of the pieces. After the initial setup is established every move made by a player is automatically detected and verified. Intel® Open Source Computer Vision Library (OpenCV) is used in the current software implementation.