Unsupervised Tree Detection and Counting via Region-Based Circle Fitting

Smaragda Markaki, Costas Panagiotakis

2023

Abstract

Automatic tree detection and counting is a very important task for many areas such as environmental protection, agricultural planning, crop yield estimation and monitoring of replanted forest areas. This paper presents an unsupervised method for tree detection from high resolution UAV imagery based on a modified version of the Decremental Ellipse Fitting Algorithm DEFA. The proposed Decremental Circle Fitting Algorithm (DCFA) works similarly to DEFA with the main difference that DCFA uses circles instead of ellipses. According to DCFA, the skeleton of the 2D shape is calculated first, followed by the initialization of the circle hypotheses and the application of the Gaussian Mixture Model Expectation Maximization algorithm. Finally, model evaluation is performed based on the Akaike Information Criterion. The DCFA method was tested on the Acacia-6 dataset, which depicts six months acacia trees, collected with Unmanned Aerial Vehicles in Southeast Asia and it exhibits high performance compared with the state-of-the art unsupervised and supervised methods.

Paper Citation

in Harvard Style

Markaki S. and Panagiotakis C. (2023). Unsupervised Tree Detection and Counting via Region-Based Circle Fitting. In Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-626-2, pages 95-106. DOI: 10.5220/0011672700003411

in Bibtex Style

@conference{icpram23,
author={Smaragda Markaki and Costas Panagiotakis},
title={Unsupervised Tree Detection and Counting via Region-Based Circle Fitting},
booktitle={Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2023},
pages={95-106},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011672700003411},
isbn={978-989-758-626-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Unsupervised Tree Detection and Counting via Region-Based Circle Fitting
SN - 978-989-758-626-2
AU - Markaki S.
AU - Panagiotakis C.
PY - 2023
SP - 95
EP - 106
DO - 10.5220/0011672700003411