Presenting an extended evaluation framework for building detection algorithms using high spatial resolution images

Document Type: Original Article


Department of Surveying Engineering, Faculty of Civil Engineering and Transportation, University of Isfahan, Isfahan, Iran


This paper aims to provide an extended evaluation framework for building detection algorithms using a diverse set of High Spatial Resolution (HSR) images. The HSR images utilized in this paper were chosen from different places and different sensors, and based on several important challenges in an urban area such as building alignment, density, shape, size, color, height, and imaging angle. The classical evaluation metrics such as detection rate, reliability, false positive rate, and overall accuracy only demonstrate the performance evaluation of an algorithm in relation to the buildings and cannot interpret the mentioned challenges. The extended evaluation framework proposed in this paper composed several extended metrics for performance evaluation of building detection algorithms in relation to these challenges in addition to the classical metrics. The paper intends to declare that the success or failure metrics of a building detection algorithm can have more varieties. In fact, a building detection algorithm may be successful at one or several metrics, whilst it may be unsuccessful at the other metrics.


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