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

Q2 Engineering
Wenting Qiao, Xiaoguang Wu, Wen Sun, Qiande Wu
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引用次数: 3

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 identi fi ed 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.
基于块阈值图像处理的混凝土梁裂缝识别算法研究
针对混凝土结构在光照不均匀、表面颜色复杂的情况下,数字图像对混凝土结构裂缝的识别精度不高的问题,本文提出了一种基于ACTIS自动检测系统获取的数字图像数据的最大熵阈值分块方法。本研究的步骤如下:1。采用日本KURABO公司的Actis系统采集混凝土梁弯曲试验中具有典型特征的混凝土试件裂纹数字图像。2. 图像被分割成块,以区分不同灰度的背景。3.采用最大类间平均灰度差法区分子块,筛选出需要分割的图像块。4. 用二维最大熵阈值分割方法对图像进行分割得到二值化图像,通过筛选二值化图像的连通域特征得到目标图像。结果表明,与其他算法相比,所提方法能有效降低图像的过分割率和欠分割率,突出目标裂缝的特征,解决背景灰度变化和光照不均匀导致的裂缝识别长度与实际长度差距过大的问题,有效提高桥梁混凝土裂缝的识别精度。
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来源期刊
SDHM Structural Durability and Health Monitoring
SDHM Structural Durability and Health Monitoring Engineering-Building and Construction
CiteScore
2.40
自引率
0.00%
发文量
29
期刊介绍: In order to maintain a reasonable cost for large scale structures such as airframes, offshore structures, nuclear plants etc., it is generally accepted that improved methods for structural integrity and durability assessment are required. Structural Health Monitoring (SHM) had emerged as an active area of research for fatigue life and damage accumulation prognostics. This is important for design and maintains of new and ageing structures.
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