{"title":"基于小波变换和数学形态学的边缘检测算法","authors":"Yujing Zhang, Qirui Han","doi":"10.1109/ICCASE.2011.5997768","DOIUrl":null,"url":null,"abstract":"Based on the combination of wavelet transform and mathematical morphology, a novel approach for the edge detection is proposed in this paper. First, detect the image edge with multi-scale adaptive wavelet threshold method, and select proper structure element for dilation operation according to the types of mathematical morphology and process the discontinuous edge. This edge detection method combines the advantages of both wavelet transform and mathematical morphology, and it can not only suppress the disturbance of the noise effectively but also keep up the consecutive and clear edges. Thus, this method is an effective algorithm for image edge detection. The experimental results show that the approach is superior to mathematical morphological method and wavelet transform method alone.","PeriodicalId":369749,"journal":{"name":"2011 International Conference on Control, Automation and Systems Engineering (CASE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Edge Detection Algorithm Based on Wavelet Transform and Mathematical Morphology\",\"authors\":\"Yujing Zhang, Qirui Han\",\"doi\":\"10.1109/ICCASE.2011.5997768\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the combination of wavelet transform and mathematical morphology, a novel approach for the edge detection is proposed in this paper. First, detect the image edge with multi-scale adaptive wavelet threshold method, and select proper structure element for dilation operation according to the types of mathematical morphology and process the discontinuous edge. This edge detection method combines the advantages of both wavelet transform and mathematical morphology, and it can not only suppress the disturbance of the noise effectively but also keep up the consecutive and clear edges. Thus, this method is an effective algorithm for image edge detection. The experimental results show that the approach is superior to mathematical morphological method and wavelet transform method alone.\",\"PeriodicalId\":369749,\"journal\":{\"name\":\"2011 International Conference on Control, Automation and Systems Engineering (CASE)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Control, Automation and Systems Engineering (CASE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCASE.2011.5997768\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Control, Automation and Systems Engineering (CASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCASE.2011.5997768","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Edge Detection Algorithm Based on Wavelet Transform and Mathematical Morphology
Based on the combination of wavelet transform and mathematical morphology, a novel approach for the edge detection is proposed in this paper. First, detect the image edge with multi-scale adaptive wavelet threshold method, and select proper structure element for dilation operation according to the types of mathematical morphology and process the discontinuous edge. This edge detection method combines the advantages of both wavelet transform and mathematical morphology, and it can not only suppress the disturbance of the noise effectively but also keep up the consecutive and clear edges. Thus, this method is an effective algorithm for image edge detection. The experimental results show that the approach is superior to mathematical morphological method and wavelet transform method alone.