Fig. 1 Automatic crack detection process flowchart.
Fig. 2 Image acquisition system for capture a railway concrete track
Fig. 3 Gausian filters factor from Gabor Filter Bank
Fig. 4 ACTCAS Program for capture a railway concrete track
Fig. 5 Experimental results from the proposed automatic crack detection process
Table 1. Results of evaluation of the automatic crack detection process
참고문헌
- Bibiloni, P., Gonzalez-Hidalgo, M., Massanet, S. (2016). "A survey on curvilinear object segmentation in multiple applications. Pattern Recognition", 60, 949-970. https://doi.org/10.1016/j.patcog.2016.07.023
- Frangi, A.F., Niessen, W.J., Vincken, K.L., Viergever, M.A. (1998). "Multiscale vessel enhancement filtering. International Conference on Medical Image Computing and Computer-Assisted Intervention." Springer, pp. 130-137.
- Hoover, A., Kouznetsova, V., Goldbaum, M. (2000). "Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response." IEEE Transactions on Medical imaging, 19, 203-210. https://doi.org/10.1109/42.845178
- Martinez-Perez, M.E., Hughes, A.D., Thom, S.A., Bharath, A.A., Parker, K.H. (2007). "Segmentation of blood vessels from red-free and fluorescein retinal images." Medical image analysis, 11, 47-61. https://doi.org/10.1016/j.media.2006.11.004
- Mendonca, A.M., Campilho, A. (2006). "Segmentation of retinal blood vessels by combining the detection of enterlines and morphological reconstruction." IEEE transactions on medical imaging, 25, 1200-1213. https://doi.org/10.1109/TMI.2006.879955
- Lacoste, C., Descombes, X., Zerubia, J. (2005). "Point processes for unsupervised line network extraction in remote sensing." IEEE Transactions on pattern analysis and machine intelligence, 27, 1568-1579. https://doi.org/10.1109/TPAMI.2005.206
- Lafarge, F., Descombes, X., others. (2010). "Geometric feature extraction by a multimarked point process." IEEE transactions on pattern analysis and machine intelligence, 32, 1597-1609. https://doi.org/10.1109/TPAMI.2009.152
- Verdié, Y., Lafarge, F. (2012). "Efficient Monte Carlo sampler for detecting parametric objects in large scenes." Computer Vision-ECCV, pp. 539-552.
- Chai, D., Forstner, W., Lafarge, F. (2013). "Recovering line-networks in images by junction-point processes." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1894-1901.
- Turetken, E., Benmansour, F., Andres, B., Glowacki, P., Pfister, H., Fua, P. (2016). "Reconstructing curvilinear networks using path classifiers and integer programming." IEEE transactions on pattern analysis and machine intelligence, 38, 2515-2530. https://doi.org/10.1109/TPAMI.2016.2519025
- Niemeijer, M., Staal, J., van Ginneken, B., Loog, M., Abramoff, M.D., others. (2004). "Comparative study of retinal vessel segmentation methods on a new publicly available database." SPIE medical imaging. SPIE, Vol. 5370, pp. 648- 656.
- Staal, J., Abràmoff, M.D., Niemeijer, M., Viergever, M.A., Van Ginneken, B. (2004). "Ridge-based vessel segmentation in color images of the retina." IEEE transactions on medical imaging, 23, 501-509. https://doi.org/10.1109/TMI.2004.825627
- Soares, J.V., Leandro, J.J., Cesar, R.M., Jelinek, H.F., Cree, M.J. (2006) "Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification." IEEE Transactions on medical Imaging, 25, 1214-1222. https://doi.org/10.1109/TMI.2006.879967
- Liskowski, P., Krawiec, K. (2016). "Segmenting Retinal Blood Vessels With Deep Neural Networks." IEEE transactions on medical imaging, 35, 2369-2380. https://doi.org/10.1109/TMI.2016.2546227
- Rabih, A., Sylvie, C., Jerome, I. (2016). "Automatic Crack Detection on Two-Dimensional Pavement Images: An Algorithm Based on Minimal Path Selection." IEEE transactions on intelligent transportation Systems, vol.17, 2718-2729 https://doi.org/10.1109/TITS.2015.2477675
- SangWan Hong., YoungJin Park., HaCheol Lee. (2014). "Experimental and Analytical Study on the Water Level Detection and Early Warning System with Intelligent CCTV" KOSDI Journal of the Korea Society of Disaster Information, vol.10, pp. 105-115 https://doi.org/10.15683/kosd.2014.10.1.105