Suárez, IagoBuenaposada, José M.Baumela, Luis2023-09-202023-09-202022Iago Suárez, José M. Buenaposada, Luis Baumela, ELSED: Enhanced line SEgment drawing, Pattern Recognition, Volume 127, 2022, 108619, ISSN 0031-3203, https://doi.org/0031-3203https://hdl.handle.net/10115/24411This work was supported by Doctorado Industrial grant DI-16-08966 and MINECO project TIN2016-75982-C2-2-R.Detecting local features, such as corners, segments or blobs, is the first step in the pipeline of many Computer Vision applications. Its speed is crucial for real-time applications. In this paper we present ELSED, the fastest line segment detector in the literature. The key for its efficiency is a local segment growing algorithm that connects gradient-aligned pixels in presence of small discontinuities. The proposed algorithm not only runs in devices with very low end hardware, but may also be parametrized to foster the detection of short or longer segments, depending on the task at hand. We also introduce new metrics to evaluate the accuracy and repeatability of segment detectors. In our experiments with different public benchmarks we prove that our method accounts the highest repeatability and it is the most efficient in the literature.1 In the experiments we quantify the accuracy traded for such gain.engAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Image edge detectionEfficient line segment detectionLine segment detection evaluationinfo:eu-repo/semantics/article10.1016/j.patcog.2022.108619info:eu-repo/semantics/openAccess