Multiresolution Information Mining for Pavement Crack Image Analysis

Author:

Adu-Gyamfi Y. O.1,Okine N. O. Attoh2,Garateguy Gonzalo3,Carrillo Rafael4,Arce Gonzalo R.5

Affiliation:

1. Graduate Student, Dept. of Civil and Environmental Engineering, Univ. of Delaware, Newark, DE 19716.

2. Professor, Dept. of Civil and Environmental Engineering, Univ. of Delaware, Newark, DE 19716 (corresponding author).

3. Graduate Student, Dept. of Electrical and Computer Engineering, Univ. of Delaware, Newark, DE 19716.

4. Institute of Electrical Engineering, Ecole Polytechnique Federale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland.

5. Professor, Dept. of Electrical and Computer Engineering, Univ. of Delaware, Newark, DE 19716.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Reference19 articles.

1. Analysis of Edge-Detection Techniques for Crack Identification in Bridges

2. Critical Analysis of Different Hilbert-Huang Algorithms for Pavement Profile Evaluation

3. Ahmed M. F. M. and Haas C. T. (2010). “Potential of low-cost close-range photogrammetry toward unified automatic pavement distress surveying.” Transportation Research Board Annual Meeting (CD-ROM) Transportation Research Board Washington DC.

4. Evaluating pavement cracks with bidimensional empirical mode decomposition;Ayenu-Prah A.,;EURASIP J. Adv. Signal Process.,2008

5. Bhagavatula R. and Savvides M. (2007). “Analyzing facial images using empirical mode decomposition for illumination artifact removal and improved face recognition.” IEEE Int. Conf. on Acoustics Speech and Signal Processing Honolulu HI 1520-61491(15–20) 501–508.

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