@inproceedings{ba8197c3dfcf402d8f965cb540391689,
title = "Crater detection using CGC A new circle detection method",
abstract = "{"}Constrained Gradient for Circle{"} (CGC) is a new circle detection algorithm based on the gradient of the intensity image. The method relies on two conditions. The {"}gradient angle compatibility condition{"} constrains the gradient of a given percentage of the pixels belonging to some digital circles having a radius in the range of radii to detect to point towards the centre of the circle or in the opposite direction. The {"}curvature compatibility condition{"} constrains the variation of the gradient angle of the same pixels in a range depending on the radius of the circle. These two conditions are sufficient to detect the core of circular shapes. The best-fitting circle is then identified. The method is applied to artificial and reference images and compared to state-of-the-art methods. It is also applied to water-filled crater detection in Cambodia: these craters that might indicate the presence of Unexploded Ordnance (UXO) dating from the US bombing produce dark circles on satellite panchromatic images.",
keywords = "Circle detection, Constrained gradient, Crater detection, Feature extraction",
author = "Vinciane Lacroix and Sabine Vanhuysse",
year = "2015",
doi = "10.5220/0005222503200327",
language = "English",
series = "ICPRAM 2015 - 4th International Conference on Pattern Recognition Applications and Methods, Proceedings",
publisher = "SciTePress",
pages = "320--327",
editor = "\{De Marsico\}, Maria and Mario Figueiredo and Ana Fred",
booktitle = "ICPRAM 2015 - 4th International Conference on Pattern Recognition Applications and Methods, Proceedings",
note = "4th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2015 ; Conference date: 10-01-2015 Through 12-01-2015",
}