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Research Article
Investigation of concrete crack Quantification Based upon Geometry Duplicate
K Santhosh Kumar1
J Bhavana2
M Mahesh3
1Dept. of Civil, G.L. Bajaj Group of Institutions, Mathura-281406, U.P., India. 23 Dept. of Civil, Mandalay Institute of Management & Technology, Greater Noida-201310, U.P., India.
Published Online: May-June 2021
Pages: 07-09
Cite this article
No DOIReferences
1. JahanshahiMR,MasriSF“A new methodology or non-contact accurate crack width measurement through photo grammetry for automated structural safety evaluation” Smart Materials and structures,22(3),2013
2. SalmanM,MathavanSKamalK,Rahman“Pavement crack detection using the Gabor filter” In:16th international IEEE conference on
intelligent transportation systems: intelligent transportation systems for all modes,2013
3. ShenY,J-WDang,Y-PWang,SunFeng.“Acompressedsensingpavement distress image filtering algorithm based on NSCT
domain”.JournalofOptoelectronicsLaser,25(8),2014,pp 1620-1626.
4. Tsai YC, Kaul V, Lettsome CA “Enhanced adaptive filter-bank-basedautomated pavement crack detection and segmentation system”
JournalofElectronicImaging,21 (4),2012
5. Nhat-Duc Hoang “Image Processingbased recognition of wall defects using machine learning approaches and steerable filters”
ComputationalIntelligenceandNeuroscience,2018
6. YasukeFujita,YoshihikoHamamoto“ARobustAutomaticcrackdetection method from noisy concrete surfaces” Machine vision
andapplications, 22(2),2011,pp 245-254
7. Gajanan K Choudhary, SayanDev “Crack detection in concrete surface using image processing,fuzzy logic and neural network”IEEE
International conference on advanced computational Intelligence,2012.
2. SalmanM,MathavanSKamalK,Rahman“Pavement crack detection using the Gabor filter” In:16th international IEEE conference on
intelligent transportation systems: intelligent transportation systems for all modes,2013
3. ShenY,J-WDang,Y-PWang,SunFeng.“Acompressedsensingpavement distress image filtering algorithm based on NSCT
domain”.JournalofOptoelectronicsLaser,25(8),2014,pp 1620-1626.
4. Tsai YC, Kaul V, Lettsome CA “Enhanced adaptive filter-bank-basedautomated pavement crack detection and segmentation system”
JournalofElectronicImaging,21 (4),2012
5. Nhat-Duc Hoang “Image Processingbased recognition of wall defects using machine learning approaches and steerable filters”
ComputationalIntelligenceandNeuroscience,2018
6. YasukeFujita,YoshihikoHamamoto“ARobustAutomaticcrackdetection method from noisy concrete surfaces” Machine vision
andapplications, 22(2),2011,pp 245-254
7. Gajanan K Choudhary, SayanDev “Crack detection in concrete surface using image processing,fuzzy logic and neural network”IEEE
International conference on advanced computational Intelligence,2012.
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