A novel approach for thermal crack detection and quantification in structural concrete using ripplet transform

[1]  Francesco Cadini,et al.  Particle filtering‐based adaptive training of neural networks for real‐time structural damage diagnosis and prognosis , 2019, Structural Control and Health Monitoring.

[2]  Sandris Ručevskis,et al.  Multiple Damage Identification in Beam Structure Based on Wavelet Transform , 2017 .

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

[4]  Sung Ho Hwang,et al.  Estimation of crack width based on shape‐sensitive kernels and semantic segmentation , 2019, Structural Control and Health Monitoring.

[5]  A. Kassem.  Deformations of R.C.Circular Slabs in Fire Condition , 2018 .

[6]  Min Huang,et al.  Multifocus image fusion method of Ripplet transform based on cycle spinning , 2014, Multimedia Tools and Applications.

[7]  Lu Sun,et al.  Multi-scale wavelet transform filtering of non-uniform pavement surface image background for automated pavement distress identification , 2016 .

[8]  Ling Wang,et al.  Crack detection in magnetic tile images using nonsubsampled shearlet transform and envelope gray level gradient , 2017 .

[9]  R. Thangarajan,et al.  An efficient visual saliency detection model based on Ripplet transform , 2017 .

[10]  Guoqi Xing,et al.  A New Energy-Efficient Building System Based on Insulated Concrete Perforated Brick with a Sandwich , 2018, Civil Engineering Journal.

[11]  R. S. Anand,et al.  Despeckling of ultrasound medical images using ripplet domain nonlinear filtering , 2013, Signal, Image and Video Processing.

[12]  Qingming Zhan,et al.  An IHS-Based Pan-Sharpening Method for Spectral Fidelity Improvement Using Ripplet Transform and Compressed Sensing , 2018, Sensors.

[13]  J. Anitha,et al.  Performance enhanced ripplet transform based compression method for medical images , 2019, Measurement.

[14]  M. El-Feky,et al.  Flexural Behavior of Unbounded Pre-stressed Beams Modified With Carbon Nanotubes under Elevated Temperature , 2019, Civil Engineering Journal.

[15]  Hui Li,et al.  Identification framework for cracks on a steel structure surface by a restricted Boltzmann machines algorithm based on consumer‐grade camera images , 2018 .

[16]  Pei-yan Shan,et al.  Subacute Combined Degeneration, Pernicious Anemia and Gastric Neuroendocrine Tumor Occured Simultaneously Caused by Autoimmune Gastritis , 2019, Front. Neurosci..

[17]  Hoang-Nam Nguyen,et al.  An Automatic Approach for Accurate Edge Detection of Concrete Crack Utilizing 2D Geometric Features of Crack , 2014, J. Signal Process. Syst..

[18]  R. Thangarajan,et al.  RTS-ELM: an approach for saliency-directed image segmentation with ripplet transform , 2019, Pattern Analysis and Applications.

[19]  Ashutosh Bagchi,et al.  Image-based retrieval of concrete crack properties for bridge inspection , 2014 .

[20]  R. S. Anand,et al.  Ripplet domain non-linear filtering for speckle reduction in ultrasound medical images , 2014, Biomed. Signal Process. Control..

[21]  Arun Kumar Sangaiah,et al.  Face expression recognition system based on ripplet transform type II and least square SVM , 2017, Multimedia Tools and Applications.

[22]  L. Kiemeney,et al.  Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study , 2017, PloS one.

[23]  Guomin Zhang,et al.  A method of detecting the cracks of concrete undergo high-temperature , 2018 .

[24]  Hamid Reza Shahdoosti,et al.  Combined ripplet and total variation image denoising methods using twin support vector machines , 2018, Multimedia Tools and Applications.

[25]  M. Barzegar,et al.  Increasing the Thermal Efficiency of Double Tube Heat Exchangers by Using Nano Hybrid , 2018 .

[26]  Daniel Paul Thanaraj,et al.  Post-fire damage assessment and capacity based modeling of concrete exposed to elevated temperature , 2020, International Journal of Damage Mechanics.

[27]  Lei Yang,et al.  Ripplet: A new transform for image processing , 2010, J. Vis. Commun. Image Represent..

[28]  Ayan Sadhu,et al.  A literature review of next‐generation smart sensing technology in structural health monitoring , 2019, Structural Control and Health Monitoring.

[29]  Malay Kumar Kundu,et al.  A Ripplet Transform Based Statistical Framework for Natural Color Image Retrieval , 2013, ICIAP.

[30]  Nhat-Duc Hoang,et al.  Detection of Surface Crack in Building Structures Using Image Processing Technique with an Improved Otsu Method for Image Thresholding , 2018 .

[31]  Francesca Odone,et al.  Edges and Corners With Shearlets , 2015, IEEE Transactions on Image Processing.

[32]  Hassan Ghassemian,et al.  Remote Sensing Image Fusion Using Ripplet Transform and Compressed Sensing , 2015, IEEE Geoscience and Remote Sensing Letters.

[33]  Khurram Kamal,et al.  Pavement crack detection using the Gabor filter , 2013, 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013).

[34]  Eduardo Júlio,et al.  Automatic mapping of cracking patterns on concrete surfaces with biological stains using hyper‐spectral images processing , 2019, Structural Control and Health Monitoring.

[35]  Jiang Honghai,et al.  Detection of surface crack defects on ferrite magnetic tile , 2014 .

[36]  Ajay Chourasia,et al.  Damage Identification of RC Structures Using Wavelet Transformation , 2016 .

[37]  Fan Xi,et al.  Detection crack in image using Otsu method and multiple filtering in image processing techniques , 2016 .

[38]  Yun Yong Kim,et al.  Automated image processing technique for detecting and analysing concrete surface cracks , 2013 .

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

[40]  Dong Lei,et al.  Experimental study on alarming of concrete micro-crack initiation based on wavelet packet analysis , 2017 .

[41]  Shivprakash Iyer,et al.  A robust approach for automatic detection and segmentation of cracks in underground pipeline images , 2005, Image Vis. Comput..

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

[43]  Masayuki Kohiyama,et al.  Detection method of unlearned pattern using support vector machine in damage classification based on deep neural network , 2020, Structural Control and Health Monitoring.

[44]  Min Xu,et al.  Segmentation of non-stochastic surfaces based on non-subsampled contourlet transform and mathematical morphologies , 2016 .