Tree Detection with Decremental Circle Fitting Algorithm
Version 1.0.0 (292 KB) by
Costas Panagiotakis
The proposed Decremental Circle Fitting Algorithm (DCFA) is applied on the tree detection problem.
This work 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.
This code is a simple implementation of DCFA method based on the paper [1].
You can find more details in www.csd.uoc.gr/~cpanag
Files:
runDCFA.m: implemetation of the method
We will appreciate if you cite our paper [1] in your work:
[1] S. Markaki, C. Panagiotakis, Unsupervised Tree Detection and Counting via Region-based Circle Fitting, International Conference on Pattern Recognition Applications and Methods (ICPRAM), 2023.
Cite As
Costas Panagiotakis (2024). Tree Detection with Decremental Circle Fitting Algorithm (https://www.mathworks.com/matlabcentral/fileexchange/126325-tree-detection-with-decremental-circle-fitting-algorithm), MATLAB Central File Exchange. Retrieved .
S. Markaki, C. Panagiotakis, Unsupervised Tree Detection and Counting via Region-based Circle Fitting, International Conference on Pattern Recognition Applications and Methods (ICPRAM), 2023.
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1.0.0 |