Crack Detection Using Enhanced Thresholding on UAV based Collected Images

This paper proposes a thresholding approach for crack detection in an unmanned aerial vehicle (UAV) based infrastructure inspection system. The proposed algorithm performs recursively on the intensity histogram of UAV-taken images to exploit their crack-pixels appearing at the low intensity interval. A quantified criterion of interclass contrast is proposed and employed as an object cost and stop condition for the recursive process. Experiments on different datasets show that our algorithm outperforms different segmentation approaches to accurately extract crack features of some commercial buildings.

[1]  Tran Hiep Dinh,et al.  Enhanced discrete particle swarm optimization path planning for UAV vision-based surface inspection , 2017, ArXiv.

[2]  N. Otsu A threshold selection method from gray level histograms , 1979 .

[3]  Chen-Ming Kuo,et al.  Unmanned Aircraft Systems for Remote Building Inspection and Monitoring , 2012 .

[4]  Shengyong Chen,et al.  Visual impact enhancement via image histogram smoothing and continuous intensity relocation , 2011, Comput. Electr. Eng..

[5]  Tran Hiep Dinh,et al.  Angle-Encoded Swarm Optimization for UAV Formation Path Planning , 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[6]  Martin D. Levine,et al.  Dynamic Measurement of Computer Generated Image Segmentations , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Hung Manh La,et al.  Automated robotic monitoring and inspection of steel structures and bridges , 2017, Robotica.

[8]  Paola Campadelli,et al.  Quantitative evaluation of color image segmentation results , 1998, Pattern Recognit. Lett..

[9]  Paulo Lobato Correia,et al.  Automatic Road Crack Detection and Characterization , 2013, IEEE Transactions on Intelligent Transportation Systems.

[10]  Jérôme Idier,et al.  Automatic Crack Detection on Two-Dimensional Pavement Images: An Algorithm Based on Minimal Path Selection , 2016, IEEE transactions on intelligent transportation systems (Print).

[11]  Zhong Yang,et al.  A New Iterative Triclass Thresholding Technique in Image Segmentation , 2014, IEEE Transactions on Image Processing.

[12]  Raja Sengupta,et al.  Vision-Based Monitoring of Locally Linear Structures Using an Unmanned Aerial Vehicle , 2008 .

[13]  Guido Morgenthal,et al.  Unmanned aerial vehicles (UAV) for the assessment of existing structures , 2013 .

[14]  Matti Pietikäinen,et al.  Adaptive document image binarization , 2000, Pattern Recognit..

[15]  Tarek Hamel,et al.  A UAV for bridge inspection: Visual servoing control law with orientation limits , 2007 .

[16]  Fan Meng,et al.  Automatic Road Crack Detection Using Random Structured Forests , 2016, IEEE Transactions on Intelligent Transportation Systems.

[17]  Mu-Chun Su,et al.  A self organizing map optimization based image recognition and processing model for bridge crack inspection , 2017 .