Robust Image-based Crack Detection in Concrete Structures Images using Multi-Scale Enhancement and Visual Features
Conference Paper, Proceedings of IEEE International Conference on Image Processing (ICIP '17), pp. 2304 - 2308, September, 2017
Abstract
In order to improve the robustness of the crack detection in the complex background, a new crack detection framework based on multi-scale enhancement and visual features is developed. Firstly, to deal with the effect of low contrast, a multi-scale enhancement method using guided filter and gradient information is proposed to get the enhanced image. Then, the adaptive threshold algorithm is used to obtain the binary image. Finally, the combination of morphological processing and visual features are adopted to purify the cracks. The experimental results with different images of real concrete surfaces demonstrate the high robustness and validity of the developed technique.
BibTeX
@conference{Liu-2017-24556,author = {Xiangzeng Liu and Yunfeng Ai and Sebastian Scherer},
title = {Robust Image-based Crack Detection in Concrete Structures Images using Multi-Scale Enhancement and Visual Features},
booktitle = {Proceedings of IEEE International Conference on Image Processing (ICIP '17)},
year = {2017},
month = {September},
pages = {2304 - 2308},
keywords = {Crack detection, guided filter, image enhancement, concrete structure},
}
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.