Methods for segmenting cracks in 3d images of concrete: A comparison based on semi-synthetic images Tin Barisin a,b Christian Jung b Franziska M¨ usebeck b Claudia Redenbach b Katja Schladitz a a Fraunhofer Institut f¨ ur Techno- und Wirtschaftsmathematik Fraunhofer-Platz 1, 67663 Kaiserslautern, Germany b Technische Universit¨ at Kaiserslautern Gottlieb-Daimler-Straße 48, 67663 Kaiserslautern, Germany Abstract Concrete is the standard construction material for buildings, bridges, and roads. As safety plays a central role in the design, monitoring, and maintenance of such constructions, it is important to understand the cracking behavior of concrete. Computed tomography captures the microstructure of building materials and allows to study crack initiation and propagation. Manual segmentation of crack surfaces in large 3d images is not feasible. In this paper, automatic crack seg- mentation methods for 3d images are reviewed and compared. Classical image processing methods (edge detection filters, template matching, minimal path and region growing algorithms) and learning methods (convolutional neural net- works, random forests) are considered and tested on semi-synthetic 3d images. Their performance strongly depends on parameter selection which should be ad- apted to the grayvalue distribution of the images and the geometric properties of the concrete. In general, the learning methods perform best, in particular for thin cracks and low grayvalue contrast. Keywords: computed tomography, fractional Brownian surface, 3d segmenta- tion, crack detection, machine learning, deep learning 1 Introduction As a building material, concrete needs to meet high standards regarding quality and sustainability. Therefore, investigating its performance under stress is an important field of research. Typically, the strength of concrete specimens is studied via stress tests that result in the formation of cracks. For instance, cracks in drill cores from vibrating beams without and with previous damage 1 arXiv:2112.09493v1 [cs.CV] 17 Dec 2021
Methods for segmenting cracks in 3d images of concrete: A comparison based on semi-synthetic images
May 28, 2023
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Related Documents
