Semnan University Press Journal of Modeling and Simulation in Electrical and Electronics Engineering 2821-0786 1 1 2021 05 01 Introducing An Efficient Set of High Spatial Resolution Images of Urban Areas to Evaluate Building Detection Algorithms 43 48 2831 10.22075/mseee.2018.911.1042 EN Iman Khosravi University of Tehran, College of Engineering, Faculty of Surveying and Geoinformation Engineering, Remote Sensing Department Mehdi Momeni University of Isfahan Journal Article 2015 09 07 The present work aims to introduce an efficient set of high spatial resolution (HSR) images to evaluate building detection algorithms more fairly. The introduced images are chosen from two recent HSR sensors (QuickBird and GeoEye-1) and based on several challenges of urban areas encountered in building detection such as diversity in building density, building dissociation, building shape, building size, building alignment, building roof color, building height, and imaging angle. To practically examine the proposed dataset, three-building detection algorithms with different strategies are employed. The results imply the proposed dataset can be helpful to more fairly evaluate each algorithm, so that it indicates where the algorithm can be efficient and successful and where may be encountered with the problems in detecting buildings in urban areas.  https://mseee.semnan.ac.ir/article_2831_f9e85303d8b436f1a37ee11a51142b36.pdf