Objectives of the methods

Ying and Salari (2010) [9]

Beamlet Transforms (BT)

Extraction of curvilinear features of crack from pavement images.

Hough (1962) [10]

Hough Transform (HT)

Recognize complex pattern in a picture.

Leymarie and Levine (1992) [11]

Grassfire Transform (GT)

Describe planer object shape including region and boundary features.

Canny (1986) [12]

Laplacian of Gaussian (LOG) operator

For edge detection.

Witkin (1984) [13]

Scale-space filtering

Precisely localize a large-scale structure using the gaussian convolution.

Sobel [14]

Sobel operator

The pixel-level edge detection algorithm.

Pallotta (2014) [15]

Zernike moments operator

Compute all the edge parameters for subpixel detection.

Ying-Dong et al. (2005) [16]

Sobel-Zernike moments operator

A fast subpixel edge detection method.

Dong, W (2008) [17]

Prewitt method

Wall crack assessment from image.

Jianzhuang et al. (1991) [18]

Otsu method

Classify the image into background and foreground and find the threshold value to minimize the variances.

Farhidzadeh et al. (2013) [19]

fractal method

Reinforcement concrete damage assessment.

Massaro, E., & Bagnoli, F. (2014) [20]

Percolation method

Large-size concrete surface crack detection method [21] - [32] .

Pudney (1998) [33]

Distance-ordered homotopic thinning (DOHT)

Distance-ordered homotopic thinning (DOHT) is effective and efficient Skeletonization Algorithm to verify a real and synthetic 3D image.

Fortune, S. (1987) [34]

Voronoi diagram

Exact shape analysis and accurate skeleton approximation.

Choi et al. (2003) [35]

Euclidean skeleton

Efficient and accurate skeletonization method.

Jia and Tang (2003) [36]

ND tensor voting

Can apply roughly homogenous and periodic textures images.