A novel, efficient image processing method is proposed here for extraction of pavement cracks from fuzzy and discontinuous pavement images. Pavement surface images obtained by CCD array, where pavement cracks are often blurry and discontinuous due to particle materials of pavement surface, crack degradation and unreliable crack shadows. Firstly, A series of preprocessing including using histogram specification, dealing with Canny-HBT filter, brightness non-uniformity correction and contrast enhancement are implemented, as the aim is to enhance the differences between cracks and backgrounds; Then a multi-scale curvelet transform is presented to obtain multiple resolution image representation, using multi-resolution method which could reserve more geometric characteristics of images, and the reliability and precision of the crack detection were improved to a large extent; Finally, the use of the Max-Mean fusion operations which consist of the dilation, erosion and thin are performed on the obtained image, and making threshold decision on the cracks connected area to realize the fine cracks fusion. The proposed system which can effectively extract the small cracks and the cracks with the weak contrast, and it has strong robustness and practical value, gives improved edge detection in images with superior edge localization and gains higher PSNR.
[1]
Madhu S. Nair,et al.
A Novel Approach for Edge Detection Using HBT Filter and Logarithmic Transform
,
2009,
2009 International Conference on Digital Image Processing.
[2]
Qingquan Li,et al.
FoSA: F* Seed-growing Approach for crack-line detection from pavement images
,
2011,
Image Vis. Comput..
[3]
Fereidoon Moghadas Nejad,et al.
A comparison of multi-resolution methods for detection and isolation of pavement distress
,
2011,
Expert Syst. Appl..
[4]
Jian Lin Yu,et al.
A Jointed Image Fusion Algorithm of Two-Dimensional PCA and Curvelet Transform
,
2013
.
[5]
Sim Heng Ong,et al.
A Luminance- and Contrast-Invariant Edge-Similarity Measure
,
2006,
IEEE Transactions on Pattern Analysis and Machine Intelligence.
[6]
Dang Jian-wu.
Pavement crack detection method based on multi-image and multi-resolution
,
2013
.
[7]
U. C. Pati,et al.
A novel technique for wall crack detection using image fusion
,
2013,
2013 International Conference on Computer Communication and Informatics.
[8]
Hao Wang,et al.
Edge texture feature extraction and expression recognition based on curvelet
,
2013,
Ifost.