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Research on Concrete Beam Crack Recognition Algorithm Based on Block Threshold Value Image Processing
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作者 Wenting Qiao Xiaoguang Wu +1 位作者 Wen Sun Qiande Wu 《Structural Durability & Health Monitoring》 EI 2020年第4期355-374,共20页
To solve the problem that the digital image recognition accuracy of concrete structure cracks is not high under the condition of uneven ill umination and complex surface color of concrete structure,this paper has prop... To solve the problem that the digital image recognition accuracy of concrete structure cracks is not high under the condition of uneven ill umination 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 fea-tures 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 dis-tinguish backgrounds of different grayscale.3.The max imum 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 max imum 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 algo-rithms,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 ilumnination,and effectively improve the recognition accuracy of bridge concrete cracks. 展开更多
关键词 Concrete crack block segmentation maximum entropy segmentation algorithms maximum interclass variance(otsu)method
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