Artigo Revisado por pares

An improved RANSAC algorithm for extracting roof planes from airborne lidar data

2019; Wiley; Volume: 35; Issue: 169 Linguagem: Inglês

10.1111/phor.12296

ISSN

1477-9730

Autores

Sibel Canaz, Fevzi Karslı,

Tópico(s)

Automated Road and Building Extraction

Resumo

Abstract The extraction of building roof planes from lidar data has become a popular research topic with random sample consensus ( RANSAC ) being one of the most commonly adopted algorithms. RANSAC extracts full planes, which is problematic when there are other points outside the plane boundary but within the plane space. This study proposes an improved RANSAC (I‐ RANSAC ) algorithm by removing points that do not belong to the roof plane. I‐ RANSAC selects a random point from the extracted roof plane and then searches for its neighbours within a given threshold to identify and remove outliers. The new algorithm was tested with 14 buildings from two datasets, where quality control measures showed significant improvement over standard RANSAC .

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