{"title":"扩展和重构经典滤波器的边缘映射响应","authors":"Ciprian Orhei, V. Bogdan, C. Bonchis","doi":"10.1109/SYNASC51798.2020.00039","DOIUrl":null,"url":null,"abstract":"Edge detection is a basic technique of fundamental feature detection in image processing domain. Dilation of edge filters kernels has proven to bring benefits for the edge detection operation by permitting to filter out noise and to take in consideration a bigger region of the image when processing. Numerous techniques were used in the past for finding edge features, one of the most common used being finding features in lower level scale of the image pyramid. Now, naturally, we want to investigate if our dilating of the filter kernels bring similar benefits as finding edges in a lower scale pyramid level.","PeriodicalId":278104,"journal":{"name":"2020 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Edge map response of dilated and reconstructed classical filters\",\"authors\":\"Ciprian Orhei, V. Bogdan, C. Bonchis\",\"doi\":\"10.1109/SYNASC51798.2020.00039\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Edge detection is a basic technique of fundamental feature detection in image processing domain. Dilation of edge filters kernels has proven to bring benefits for the edge detection operation by permitting to filter out noise and to take in consideration a bigger region of the image when processing. Numerous techniques were used in the past for finding edge features, one of the most common used being finding features in lower level scale of the image pyramid. Now, naturally, we want to investigate if our dilating of the filter kernels bring similar benefits as finding edges in a lower scale pyramid level.\",\"PeriodicalId\":278104,\"journal\":{\"name\":\"2020 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SYNASC51798.2020.00039\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYNASC51798.2020.00039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Edge map response of dilated and reconstructed classical filters
Edge detection is a basic technique of fundamental feature detection in image processing domain. Dilation of edge filters kernels has proven to bring benefits for the edge detection operation by permitting to filter out noise and to take in consideration a bigger region of the image when processing. Numerous techniques were used in the past for finding edge features, one of the most common used being finding features in lower level scale of the image pyramid. Now, naturally, we want to investigate if our dilating of the filter kernels bring similar benefits as finding edges in a lower scale pyramid level.