Open Access
ARTICLE
Research on Concrete Beam Crack Recognition Algorithm Based on Block Threshold Value Image Processing
Wenting Qiao1,2, Xiaoguang Wu1,*, Wen Sun3, Qiande Wu4,*
1 School of Highway, Chang’an University, Xi’an, 710064, China
2 Inner Mongolia Transport Construction Engineering Quality Supervision Bureau, Hohhot, 010020, China
3 Jiangsu Fasten Material Analysis and Inspecting Co., Ltd., Jiangyin, 214446, China
4 School of Civil Engineering, Southeast University, Nanjing, 210000, China
* Corresponding Authors: Xiaoguang Wu. Email: ; Qiande Wu. Email:
Structural Durability & Health Monitoring 2020, 14(4), 355-374. https://doi.org/10.32604/sdhm.2020.011479
Received 10 May 2020; Accepted 08 July 2020; Issue published 04 December 2020
Abstract
To solve the problem that the digital image recognition accuracy of
concrete structure cracks is not high under the condition of uneven illumination
and complex surface color of concrete structure, this paper has proposed a block
segmentation method of maximum entropy threshold based on the digital image
data obtained by the ACTIS automatic detection system. The steps in this research
are as follows: 1. The crack digital images of concrete specimens with typical features were collected by using the Actis system of KURABO Co., Ltd., of Japan in
the concrete beam bending test. 2. The images are segmented into blocks to distinguish backgrounds of different grayscale. 3. The maximum interclass average
gray difference method is used to distinguish the sub-blocks and screen out the
image blocks that need to be segmented. 4. Segmentation is made to the image
with 2D maximum entropy threshold segmentation method to obtain the binary
image, and the target image can be obtained by screening the connected domain
features of the binary image. Results have shown that compared with other algorithms, the proposed method can effectively decrease the image over-segmentation
and under segmentation rates, highlight the characteristics of the target cracks, solve
the problems of excessive difference between the identified length and actual length
of cracks caused by background gray level change and uneven illumination, and
effectively improve the recognition accuracy of bridge concrete cracks.
Keywords
Cite This Article
Qiao, W., Wu, X., Sun, W., Wu, Q. (2020). Research on Concrete Beam Crack Recognition Algorithm Based on Block Threshold Value Image Processing.
Structural Durability & Health Monitoring, 14(4), 355–374.
Citations