Coastline changes are increasing rapidly due to both natural and human effects. The expansion of touristic, industrial and culture fishing establishments through coastal areas has brought about uncontrolled and unplanned urbanization. In this study, the coastline in Karasu district of Turkey has been extracted by using Unmanned Aerial Vehicle (UAV) images. For this purpose; 7 cm ground sample distance (GSD) UAV images taken in 2013 by Gatewing-X100 by 40% side and 70% forward overlap was used as post images. Produced ortho images were used as the base map for extraction of the coastline. An object-oriented approach has been applied to capture the shoreline from these ortho images. In the presented study, the eCognition object-oriented fuzzy image processing software has been used. This commercial software has the ability to develop custom tools for image classification in addition to its standard object feature tools. Customized arithmetic features have been used to achieve more accurate shoreline segmentation results. Three main object classes have been created as "sea", "shoreline buffer" and "land" to extract shoreline. The segmentation results were converted into "dxf" vector data format. The results were compared with manual digitizing of 55 blind readers. An algorithm has been developed by using Matlab to analyze the differences between object-oriented classification and manual digitizing results. Results were evaluated according to students' gender, age, spent time, used software and courses taken. The root mean square error (RMSE) was calculated as 7.15 m.