Combining Orientation Symmetry and LM Cues for the Detection of Citrus Trees in Orchards From a Digital Surface Model

OK A. Ö., ÖZDARICI OK A.

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, vol.15, no.12, pp.1817-1821, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 15 Issue: 12
  • Publication Date: 2018
  • Doi Number: 10.1109/lgrs.2018.2865003
  • Journal Name: IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1817-1821
  • Keywords: Automated detection, citrus trees, digital surface model (DSM), local maxima (LM), orientation symmetry, unmanned aerial vehicles (UAVs), CROWN DELINEATION, LIDAR DATA, SEGMENTATION, CLASSIFICATION, FOREST, LEVEL
  • Ankara Haci Bayram Veli University Affiliated: Yes

Abstract

This letter proposes a new approach for the automated detection of citrus trees from a single digital surface model (DSM) input. The new approach combines orientation symmetry information and local maxima cues in a probabilistic manner. Experiments are performed on eight test DSMs generated from unmanned aerial vehicle (UAV) images, and the results reveal that the new approach is capable of detecting citrus trees with a high success (overall F-1-score of 92.5%). The performance of our approach is also compared with leading approaches from the literature and from our own previous work and provided superior or comparable results.