Research on the Method of Detecting the Spreading Rate of the Simultaneous Crushed Stone Sealing Layer Based on Machine Vision
Synchronous chip seal is an advanced road constructing technology, and the gravel coverage rate is an important indicator of the construction quality. The traditional method to measure the gravel coverage rate usually depends on observation by human eyes, which is rough and inefficient. In this pape...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/4017071 |
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| _version_ | 1832565408208519168 |
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| author | Xin Rong Honghai Liu Xinmin Gao Qinghua Bian |
| author_facet | Xin Rong Honghai Liu Xinmin Gao Qinghua Bian |
| author_sort | Xin Rong |
| collection | DOAJ |
| description | Synchronous chip seal is an advanced road constructing technology, and the gravel coverage rate is an important indicator of the construction quality. The traditional method to measure the gravel coverage rate usually depends on observation by human eyes, which is rough and inefficient. In this paper, a detection method of gravel coverage based on improved wavelet algorithm is proposed. By decomposing the image with two-dimensional discrete wavelet, the high-frequency and low-frequency coefficients are extracted. The noise of the high-frequency coefficients in the image is removed by improving the threshold function, and the contrast of the gravel target in the low-frequency coefficients is improved by the multiscale Retinex algorithm, and then two-dimensional wavelet reconstruction is carried out. Finally, the gravel target is segmented by the block threshold method, and the pixel ratio of the gravel is calculated to complete the detection of the gravel coverage. The experimental results show that the proposed method can effectively segment the gravel target and reduce the influence of environmental factors on the detection accuracy. The detection accuracy error is within ±2%, which can meet the detection requirements. The improved wavelet algorithm improves the signal-to-noise ratio of the denoised image, reduces the mean square error, and achieves a relatively good denoising effect. |
| format | Article |
| id | doaj-art-d7976ac2ac234cc4af984935767b848d |
| institution | Kabale University |
| issn | 1687-8094 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-d7976ac2ac234cc4af984935767b848d2025-02-03T01:07:55ZengWileyAdvances in Civil Engineering1687-80942022-01-01202210.1155/2022/4017071Research on the Method of Detecting the Spreading Rate of the Simultaneous Crushed Stone Sealing Layer Based on Machine VisionXin Rong0Honghai Liu1Xinmin Gao2Qinghua Bian3Key Laboratory of Road Construction Technology and EquipmentKey Laboratory of Road Construction Technology and EquipmentResearch and Development Center of Transport Industry of TechnologiesResearch and Development Center of Transport Industry of TechnologiesSynchronous chip seal is an advanced road constructing technology, and the gravel coverage rate is an important indicator of the construction quality. The traditional method to measure the gravel coverage rate usually depends on observation by human eyes, which is rough and inefficient. In this paper, a detection method of gravel coverage based on improved wavelet algorithm is proposed. By decomposing the image with two-dimensional discrete wavelet, the high-frequency and low-frequency coefficients are extracted. The noise of the high-frequency coefficients in the image is removed by improving the threshold function, and the contrast of the gravel target in the low-frequency coefficients is improved by the multiscale Retinex algorithm, and then two-dimensional wavelet reconstruction is carried out. Finally, the gravel target is segmented by the block threshold method, and the pixel ratio of the gravel is calculated to complete the detection of the gravel coverage. The experimental results show that the proposed method can effectively segment the gravel target and reduce the influence of environmental factors on the detection accuracy. The detection accuracy error is within ±2%, which can meet the detection requirements. The improved wavelet algorithm improves the signal-to-noise ratio of the denoised image, reduces the mean square error, and achieves a relatively good denoising effect.http://dx.doi.org/10.1155/2022/4017071 |
| spellingShingle | Xin Rong Honghai Liu Xinmin Gao Qinghua Bian Research on the Method of Detecting the Spreading Rate of the Simultaneous Crushed Stone Sealing Layer Based on Machine Vision Advances in Civil Engineering |
| title | Research on the Method of Detecting the Spreading Rate of the Simultaneous Crushed Stone Sealing Layer Based on Machine Vision |
| title_full | Research on the Method of Detecting the Spreading Rate of the Simultaneous Crushed Stone Sealing Layer Based on Machine Vision |
| title_fullStr | Research on the Method of Detecting the Spreading Rate of the Simultaneous Crushed Stone Sealing Layer Based on Machine Vision |
| title_full_unstemmed | Research on the Method of Detecting the Spreading Rate of the Simultaneous Crushed Stone Sealing Layer Based on Machine Vision |
| title_short | Research on the Method of Detecting the Spreading Rate of the Simultaneous Crushed Stone Sealing Layer Based on Machine Vision |
| title_sort | research on the method of detecting the spreading rate of the simultaneous crushed stone sealing layer based on machine vision |
| url | http://dx.doi.org/10.1155/2022/4017071 |
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