Automatic mapping of cracking patterns on concrete surfaces with biological stains using hyper‐spectral images processing

[1]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Eduardo Júlio,et al.  Automatic concrete health monitoring: assessment and monitoring of concrete surfaces , 2014 .

[3]  Tomoyuki Yamaguchi,et al.  Practical image measurement of crack width for real concrete structure , 2009 .

[4]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[5]  Tara C. Hutchinson,et al.  Improved image analysis for evaluating concrete damage , 2006 .

[6]  Eduardo Júlio,et al.  Damage assessment on concrete surfaces using multi-spectral image analysis , 2013 .

[7]  Shuji Hashimoto,et al.  Fast crack detection method for large-size concrete surface images using percolation-based image processing , 2010, Machine Vision and Applications.

[8]  Branko Glisic,et al.  Crack detection and characterization techniques—An overview , 2014 .

[9]  S. Hashimoto,et al.  An efficient crack detection method using percolation-based image processing , 2008, 2008 3rd IEEE Conference on Industrial Electronics and Applications.

[10]  Tom Fawcett,et al.  An introduction to ROC analysis , 2006, Pattern Recognit. Lett..

[11]  S. P. Lloyd,et al.  Least squares quantization in PCM , 1982, IEEE Trans. Inf. Theory.

[12]  Shuji Hashimoto,et al.  Improved percolation-based method for crack detection in concrete surface images , 2008, 2008 19th International Conference on Pattern Recognition.

[13]  S. Hashimoto,et al.  Automated Crack Detection for Concrete Surface Image Using Percolation Model and Edge Information , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.

[14]  Eduardo Júlio,et al.  Characterisation of concrete cracking during laboratorial tests using image processing , 2012 .

[15]  Eduardo Júlio,et al.  Detection of cracks on concrete surfaces by hyperspectral image processing , 2017, Optical Metrology.

[16]  Yambem Jina Chanu,et al.  Image Segmentation Using K -means Clustering Algorithm and Subtractive Clustering Algorithm , 2015 .

[17]  Nikos A. Vlassis,et al.  The global k-means clustering algorithm , 2003, Pattern Recognit..

[18]  Ling Liu,et al.  The algorithm of accelerated cracks detection and extracting skeleton by direction chain code in concrete surface image , 2016 .

[19]  Shuji Hashimoto,et al.  Image‐Based Crack Detection for Real Concrete Surfaces , 2008 .

[20]  Sergei Vassilvitskii,et al.  k-means++: the advantages of careful seeding , 2007, SODA '07.

[21]  Ikhlas Abdel-Qader,et al.  ANALYSIS OF EDGE-DETECTION TECHNIQUES FOR CRACK IDENTIFICATION IN BRIDGES , 2003 .

[22]  Yoshihiko Hamamoto,et al.  A robust automatic crack detection method from noisy concrete surfaces , 2011, Machine Vision and Applications.

[23]  Analysis of Concrete Reflectance Characteristics Using Spectrometer and Vnir Hyperspectral Camera , 2012 .

[24]  Ning Wang,et al.  An improved algorithm for image crack detection based on percolation model , 2015 .

[25]  Eduardo Júlio,et al.  Automatic crack monitoring using photogrammetry and image processing , 2013 .