Authors:
Smaragda Markaki
and
Costas Panagiotakis
Affiliation:
Department of Management Science and Technology, Hellenic Mediterranean University, Agios Nikolaos, 72100, Greece
Keyword(s):
Remote Sensing, Tree Detection, Tree Counting, Circle Fitting, Vegetation Index, UAV Images, AIC.
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.
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