Open Access

ARTICLE

Research on Concrete Beam Crack Recognition Algorithm Based on Block Threshold Value Image Processing

Wenting Qiao^1,2, Xiaoguang Wu^1,*, Wen Sun³, Qiande Wu^4,*

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.

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Citations