[{"month":"05","publication_identifier":{"issn":["2212-0173"]},"day":"01","oa_version":"Published Version","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","file":[{"creator":"dernst","file_size":305426,"access_level":"open_access","relation":"main_file","content_type":"application/pdf","file_id":"5863","checksum":"ba0185986b151d8c11201f48cd505ceb","file_name":"2012_Procedia_Biswas.pdf","date_created":"2019-01-21T07:28:06Z","date_updated":"2020-07-14T12:47:12Z"}],"author":[{"full_name":"Biswas, Ranita","first_name":"Ranita","id":"3C2B033E-F248-11E8-B48F-1D18A9856A87","last_name":"Biswas","orcid":"0000-0002-5372-7890"},{"first_name":"Jaya","full_name":"Sil, Jaya","last_name":"Sil"}],"status":"public","type":"journal_article","has_accepted_license":"1","intvolume":"         4","oa":1,"date_updated":"2021-01-12T08:03:43Z","title":"An Improved Canny Edge Detection Algorithm Based on Type-2 Fuzzy Sets","publication":"Procedia Technology","language":[{"iso":"eng"}],"ddc":["000"],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","image":"/images/cc_by_nc_nd.png","short":"CC BY-NC-ND (4.0)","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)"},"abstract":[{"lang":"eng","text":"Canny's edge detection algorithm is a classical and robust method for edge detection in gray-scale images. The two \r\nsignificant features of this method are introduction of NMS (Non-Maximum Suppression) and double thresholding of \r\nthe  gradient  image.  Due  to  poor  illumination,  the  region  boundaries  in  an  image  may  become  vague,  creating  \r\nuncertainties  in  the  gradient  image.  In  this  paper,  we  have  proposed  an  algorithm  based  on  the  concept  of  type-2  fuzzy  sets  to  handle  uncertainties  that  automatically  selects  the  threshold  values  needed  to  segment  the  gradient image using classical Canny’s edge detection algorithm. The results show that our algorithm works significantly well on different benchmark images as well as medical images (hand radiography images). "}],"publication_status":"published","publisher":"Elsevier","license":"https://creativecommons.org/licenses/by-nc-nd/4.0/","date_published":"2012-05-01T00:00:00Z","page":"820-824","extern":"1","volume":4,"quality_controlled":"1","year":"2012","citation":{"apa":"Biswas, R., &#38; Sil, J. (2012). An Improved Canny Edge Detection Algorithm Based on Type-2 Fuzzy Sets. <i>Procedia Technology</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.protcy.2012.05.134\">https://doi.org/10.1016/j.protcy.2012.05.134</a>","mla":"Biswas, Ranita, and Jaya Sil. “An Improved Canny Edge Detection Algorithm Based on Type-2 Fuzzy Sets.” <i>Procedia Technology</i>, vol. 4, Elsevier, 2012, pp. 820–24, doi:<a href=\"https://doi.org/10.1016/j.protcy.2012.05.134\">10.1016/j.protcy.2012.05.134</a>.","ista":"Biswas R, Sil J. 2012. An Improved Canny Edge Detection Algorithm Based on Type-2 Fuzzy Sets. Procedia Technology. 4, 820–824.","chicago":"Biswas, Ranita, and Jaya Sil. “An Improved Canny Edge Detection Algorithm Based on Type-2 Fuzzy Sets.” <i>Procedia Technology</i>. Elsevier, 2012. <a href=\"https://doi.org/10.1016/j.protcy.2012.05.134\">https://doi.org/10.1016/j.protcy.2012.05.134</a>.","short":"R. Biswas, J. Sil, Procedia Technology 4 (2012) 820–824.","ama":"Biswas R, Sil J. An Improved Canny Edge Detection Algorithm Based on Type-2 Fuzzy Sets. <i>Procedia Technology</i>. 2012;4:820-824. doi:<a href=\"https://doi.org/10.1016/j.protcy.2012.05.134\">10.1016/j.protcy.2012.05.134</a>","ieee":"R. Biswas and J. Sil, “An Improved Canny Edge Detection Algorithm Based on Type-2 Fuzzy Sets,” <i>Procedia Technology</i>, vol. 4. Elsevier, pp. 820–824, 2012."},"date_created":"2019-01-17T11:54:21Z","doi":"10.1016/j.protcy.2012.05.134","file_date_updated":"2020-07-14T12:47:12Z","_id":"5839"}]