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Title: Improved road crack detection based on one-class Parzen density estimation and entropy reduction
Authors: Oliveira, Henrique
Caeiro, José Jasnau
Correia, Paulo
Keywords: Road crack detection
One-class classification
Entropy reduction filter
Issue Date: Sep-2010
Publisher: IEEE
Citation: [IEEE style] H. Oliveira, J. J. Caeiro, and P. L. Correia, "Improved road crack detection based on one-class Parzen density estimation and entropy reduction," in Proceedings - International Conference on Image Processing, ICIP, 2010, pp. 2201-2204.
Abstract: A novel unsupervised strategy to detect cracks on flexible road pavement images, acquired by laser imaging systems, is proposed. It explores the UINTA entropy reduction filter in an innovative way. A two stage approach is followed, after a pre-processing stage, aimed at reducing the variance of image pixel intensities. First, a one-class clustering, using Parzen density estimation, is applied to select image areas likely to contain cracks, exploiting a simple two dimensional feature space which includes the mean and standard deviation of pixel intensities computed for non-overlapping image blocks. Second, the selected blocks are filtered using the UINTA entropy reduction properties and later automatically labeled as containing cracks, or not. Encouraging experimental crack detection results are presented based on real images captured along Canadian roads.
Description: 17th IEEE International Conference on Image Processing
Peer reviewed: yes
ISBN: 978-1-4244-7994-8
Publisher version:
Appears in Collections:D-ENG - Comunicações com peer review

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