Crack detection

1. Combination Algorithm

1.1. DIC(Digital Image Correlation) & Acoustic Emission

2. Traditional Image Processing

2.1. Integrated Algorithm

2.1.1. Pre-processing

2.1.1.1. Subtraction

2.1.2. Segmentation

2.1.2.1. Line-emphasis

2.1.2.2. Edge Detection

2.1.2.3. Intensity Thresholding

2.1.2.3.1. Ostu

2.1.2.3.2. Neighboring Difference Histogram (NDHM)

2.1.2.4. Wavelet Transform

2.2. Filtering technology

2.2.1. Gabor Filtering

2.2.2. MultiFiltering with Otsu method

2.3. Morphological Approach

2.4. Percolation-based Method

2.4.1. High-Speed Percolation algorithm

2.4.2. Minimal Path Selection (MPS)

2.4.3. Crack Fundamental Element (CFE)

2.4.4. CrackTree

2.4.5. CrackHHP

3. Traditional Machine Learning

3.1. BP Neural Network

3.2. Bayesian Classifier

3.3. SVM

3.4. Boosting

3.5. CrackForest