An Automatic and Threshold-Free Performance Evaluation System for Building Extraction Techniques From Airborne LIDAR Data

Some performance evaluation systems for building extraction techniques are manual in the sense that only visual results are provided or human judgment is employed. Many evaluation systems that employ one or more thresholds to ascertain whether an extracted building or roof plane is correct are subjective and cannot be applied in general. There are only a small number of automatic and threshold-free evaluation systems, but these do not necessarily consider all special cases, e.g., when over- and under-segmentation occurs during the extraction of roof planes. This paper proposes an automatic and threshold-free evaluation system that offers robust object-based evaluation of building extraction techniques. It makes one-to-one correspondences between extracted and reference entities using the maximum overlaps. Its application to the evaluation of a building extraction technique shows that it estimates different performance indicators including segmentation errors. Consequently, it can be employed for bias-free evaluation of other techniques whose outputs consist of polygonal entities.