Evaluating pavement cracks with bidimensional empirical mode decomposition

DOI10.1155/2008/861701zbMath1184.94013DBLPjournals/ejasp/Ayenu-PrahA08OpenAlexW2008935780WikidataQ59216140 ScholiaQ59216140MaRDI QIDQ966944

Albert Ayenu-Prah, Nii Attoh-Okine

Publication date: 24 April 2010

Published in: EURASIP Journal on Advances in Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2008/861701

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (3)

Computational deep learning algorithm (vision/frequency response)-based damage detection in engineering structure ⋮ A hybrid framework for asphalt pavement rutting prediction modeling and influencing factors analysis based on multilevel wavelet decomposition and transfer entropy ⋮ Image based techniques for crack detection, classification and quantification in asphalt pavement: a review

Cites Work

• A study of the characteristics of white noise using the empirical mode decomposition method
• A confidence limit for the empirical mode decomposition and Hilbert spectral analysis
• The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
• VARIABLE SAMPLING OF THE EMPIRICAL MODE DECOMPOSITION OF TWO-DIMENSIONAL SIGNALS
• On the Canny edge detector

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