{"title":"灰色关联度与改进的八方向Sobel算子边缘检测","authors":"Yang Yang, Lian Wei","doi":"10.4236/JSIP.2021.122002","DOIUrl":null,"url":null,"abstract":"Edge \ndetection is an important aspect to improve image edge quality in image \nprocessing. The purpose of edge detection is to identify the points in digital \nimages with great brightness variation. However, the accuracy of traditional \nedge detection methods in edge extraction is low. For the actual image, the \ngrey edge is sometimes not very clear, the image also contains noise. The \ndetection result of the traditional Sobel operator is relatively accurate, but the detection \nresult is rough and sensitive to noise. To solve the above problems, this paper \nproposes an improved eight-direction Sobel operator based on grey relevancy \ndegree, which combines 5 × 5 Sobel operator with a grey relational degree and \na new eight-direction grey relevancy method. The results show that this method \ncan detect the useful information of edge more accurately and improve the \nanti-noise performance. However, the drawback is that the algorithm is not \nautomatic.","PeriodicalId":38474,"journal":{"name":"Journal of Information Hiding and Multimedia Signal Processing","volume":"6 1","pages":"43-55"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Grey Relevancy Degree and Improved Eight-Direction Sobel Operator Edge Detection\",\"authors\":\"Yang Yang, Lian Wei\",\"doi\":\"10.4236/JSIP.2021.122002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Edge \\ndetection is an important aspect to improve image edge quality in image \\nprocessing. The purpose of edge detection is to identify the points in digital \\nimages with great brightness variation. However, the accuracy of traditional \\nedge detection methods in edge extraction is low. For the actual image, the \\ngrey edge is sometimes not very clear, the image also contains noise. The \\ndetection result of the traditional Sobel operator is relatively accurate, but the detection \\nresult is rough and sensitive to noise. To solve the above problems, this paper \\nproposes an improved eight-direction Sobel operator based on grey relevancy \\ndegree, which combines 5 × 5 Sobel operator with a grey relational degree and \\na new eight-direction grey relevancy method. The results show that this method \\ncan detect the useful information of edge more accurately and improve the \\nanti-noise performance. However, the drawback is that the algorithm is not \\nautomatic.\",\"PeriodicalId\":38474,\"journal\":{\"name\":\"Journal of Information Hiding and Multimedia Signal Processing\",\"volume\":\"6 1\",\"pages\":\"43-55\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-04-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Information Hiding and Multimedia Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4236/JSIP.2021.122002\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Information Hiding and Multimedia Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4236/JSIP.2021.122002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
Grey Relevancy Degree and Improved Eight-Direction Sobel Operator Edge Detection
Edge
detection is an important aspect to improve image edge quality in image
processing. The purpose of edge detection is to identify the points in digital
images with great brightness variation. However, the accuracy of traditional
edge detection methods in edge extraction is low. For the actual image, the
grey edge is sometimes not very clear, the image also contains noise. The
detection result of the traditional Sobel operator is relatively accurate, but the detection
result is rough and sensitive to noise. To solve the above problems, this paper
proposes an improved eight-direction Sobel operator based on grey relevancy
degree, which combines 5 × 5 Sobel operator with a grey relational degree and
a new eight-direction grey relevancy method. The results show that this method
can detect the useful information of edge more accurately and improve the
anti-noise performance. However, the drawback is that the algorithm is not
automatic.