{"title":"基于分数阶积分谷边检测的路面裂缝提取","authors":"Weixing Wang, L. C. Wu","doi":"10.3969/J.ISSN.1000-565X.2014.01.020","DOIUrl":null,"url":null,"abstract":"As pavement crack images are difficult to segment due to the existence of high noise, weak boundary and small cracks, an extraction method of pavement cracks based on the valley edge detection of fractional integral is proposed. In this method, first, neighboring smoothing of the original image is performed to eliminate the noise and expand the relative width of the cracks. Then, the main cracks are extracted via the valley edge detection of fractional integral, and the resulting image is further processed via the morphological approach with short-line noise elimination. Afterwards, final cracks are extracted by using the gap linking method on maximum entropy threshold to cause cracks to merge automatically. Experimental results show that the proposed method instantly helps to detect small pavement cracks with high accuracy and strong noise robustness.","PeriodicalId":35957,"journal":{"name":"华南理工大学学报(自然科学版)","volume":"63 1","pages":"117-122"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Extraction of pavement cracks based on valley edge detection of fractional integral\",\"authors\":\"Weixing Wang, L. C. Wu\",\"doi\":\"10.3969/J.ISSN.1000-565X.2014.01.020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As pavement crack images are difficult to segment due to the existence of high noise, weak boundary and small cracks, an extraction method of pavement cracks based on the valley edge detection of fractional integral is proposed. In this method, first, neighboring smoothing of the original image is performed to eliminate the noise and expand the relative width of the cracks. Then, the main cracks are extracted via the valley edge detection of fractional integral, and the resulting image is further processed via the morphological approach with short-line noise elimination. Afterwards, final cracks are extracted by using the gap linking method on maximum entropy threshold to cause cracks to merge automatically. Experimental results show that the proposed method instantly helps to detect small pavement cracks with high accuracy and strong noise robustness.\",\"PeriodicalId\":35957,\"journal\":{\"name\":\"华南理工大学学报(自然科学版)\",\"volume\":\"63 1\",\"pages\":\"117-122\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"华南理工大学学报(自然科学版)\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.3969/J.ISSN.1000-565X.2014.01.020\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"华南理工大学学报(自然科学版)","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.3969/J.ISSN.1000-565X.2014.01.020","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
Extraction of pavement cracks based on valley edge detection of fractional integral
As pavement crack images are difficult to segment due to the existence of high noise, weak boundary and small cracks, an extraction method of pavement cracks based on the valley edge detection of fractional integral is proposed. In this method, first, neighboring smoothing of the original image is performed to eliminate the noise and expand the relative width of the cracks. Then, the main cracks are extracted via the valley edge detection of fractional integral, and the resulting image is further processed via the morphological approach with short-line noise elimination. Afterwards, final cracks are extracted by using the gap linking method on maximum entropy threshold to cause cracks to merge automatically. Experimental results show that the proposed method instantly helps to detect small pavement cracks with high accuracy and strong noise robustness.
期刊介绍:
Journal of South China University of Technology (Natural Science Edition) is a comprehensive scientific journal under the supervision of the Ministry of Education and sponsored by South China University of Technology. It was founded in 1957 and was originally named Journal of South China Institute of Technology. It was published in quarterly form before 1993 and monthly form since 1995.
The purpose of this journal is to be guided by the socialist ideology with Chinese characteristics in the new era, adhere to the basic line and basic policies of the Party, adhere to the four basic principles, and adhere to the scientific development concept; abide by the national policies, laws and regulations on science and technology and publishing, and conscientiously implement the "Regulations on Periodical Publishing Management" and "Regulations on the Management of Journals of Institutions of Higher Education"; adhere to the principle of "letting a hundred flowers bloom and a hundred schools of thought contend", serve the prosperity of academia, promote academic exchanges at home and abroad, and serve the "revitalization of the country through science and education" and the construction of socialist spiritual civilization.