Multiscale Product for Edge Detection
Many methods have been proposed to extract the most relevant areas of an image. This article explores the method of edge detection by the multiscale product （MP） of the wavelet transform. The wavelet used in this work is the first derivative of a bidimensional Gaussian function. InitiaRy, we constru...
Gespeichert in:
| Veröffentlicht in: | 电子科技学刊 2014, Vol.12 (1), p.112-115 |
|---|---|
| 1. Verfasser: | |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 115 |
|---|---|
| container_issue | 1 |
| container_start_page | 112 |
| container_title | 电子科技学刊 |
| container_volume | 12 |
| creator | Nadia Ben Youssef Aicha Bouzid Noureddine Ellouze |
| description | Many methods have been proposed to extract the most relevant areas of an image. This article explores the method of edge detection by the multiscale product （MP） of the wavelet transform. The wavelet used in this work is the first derivative of a bidimensional Gaussian function. InitiaRy, we construct the wavelet, then we present the MP approach which is applied to binary and grey levels images. This method is compared with other methods without noise and in the presence of noise. The experiment results show fhht the MP method for edge detection outPerforms conventional methods even in noisy environments. |
| doi_str_mv | 10.3969/j.issn.1674-862X.2014.01.022 |
| format | Article |
| fullrecord | <record><control><sourceid>wanfang_jour_chong</sourceid><recordid>TN_cdi_wanfang_journals_zgdzkj_e201401022</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><cqvip_id>49129061</cqvip_id><wanfj_id>zgdzkj_e201401022</wanfj_id><sourcerecordid>zgdzkj_e201401022</sourcerecordid><originalsourceid>FETCH-LOGICAL-c602-62dfd2142ee5a4d916b895ba07c30f87fc835a0f64e5cd93cc62c8659753acde3</originalsourceid><addsrcrecordid>eNo9j0tLxDAYRbNQcBjnP1TQhYvGPL80SxnHB4zoYhbuSppHTa2tNi3i_HorI64uXA73chA6pwRzDfqqwTGlDlNQIi-AvWBGqMCEYsLYEVr89ydolVKsiKQcFCi2QBePUzvGZE3rs-ehd5Mds9AP2cbVPrvxo7dj7LtTdBxMm_zqL5dod7vZre_z7dPdw_p6m1sgLAfmgmNUMO-lEU5TqAotK0OU5SQUKtiCS0MCCC-t09xaYLYAqZXkxjrPl-jyMPtlumC6umz6aejmw3Jfu_1bU_pfL0Jnq5k9O7D2te_qzzjTH0N8N8N3KTRlmgDlP1h_UPY</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Multiscale Product for Edge Detection</title><source>Alma/SFX Local Collection</source><creator>Nadia Ben Youssef Aicha Bouzid Noureddine Ellouze</creator><creatorcontrib>Nadia Ben Youssef Aicha Bouzid Noureddine Ellouze</creatorcontrib><description>Many methods have been proposed to extract the most relevant areas of an image. This article explores the method of edge detection by the multiscale product （MP） of the wavelet transform. The wavelet used in this work is the first derivative of a bidimensional Gaussian function. InitiaRy, we construct the wavelet, then we present the MP approach which is applied to binary and grey levels images. This method is compared with other methods without noise and in the presence of noise. The experiment results show fhht the MP method for edge detection outPerforms conventional methods even in noisy environments.</description><identifier>ISSN: 1674-862X</identifier><identifier>DOI: 10.3969/j.issn.1674-862X.2014.01.022</identifier><language>eng</language><publisher>the Signal, Image, and Information Technology Laboratory, Department of Electrical Engineering, National Engineering School of Tunis, Tunis, Tunisia%the Department of Electrical Engineering, National Engineering School of Tunis, Tunis, Tunisia</publisher><subject>一阶导数 ; 产品 ; 传统方法 ; 多尺度边缘检测 ; 小波 ; 灰度级 ; 高斯函数</subject><ispartof>电子科技学刊, 2014, Vol.12 (1), p.112-115</ispartof><rights>Copyright © Wanfang Data Co. Ltd. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://image.cqvip.com/vip1000/qk/87980A/87980A.jpg</thumbnail><link.rule.ids>314,780,784,4024,27923,27924,27925</link.rule.ids></links><search><creatorcontrib>Nadia Ben Youssef Aicha Bouzid Noureddine Ellouze</creatorcontrib><title>Multiscale Product for Edge Detection</title><title>电子科技学刊</title><addtitle>Journal of Electronic Science Technology</addtitle><description>Many methods have been proposed to extract the most relevant areas of an image. This article explores the method of edge detection by the multiscale product （MP） of the wavelet transform. The wavelet used in this work is the first derivative of a bidimensional Gaussian function. InitiaRy, we construct the wavelet, then we present the MP approach which is applied to binary and grey levels images. This method is compared with other methods without noise and in the presence of noise. The experiment results show fhht the MP method for edge detection outPerforms conventional methods even in noisy environments.</description><subject>一阶导数</subject><subject>产品</subject><subject>传统方法</subject><subject>多尺度边缘检测</subject><subject>小波</subject><subject>灰度级</subject><subject>高斯函数</subject><issn>1674-862X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNo9j0tLxDAYRbNQcBjnP1TQhYvGPL80SxnHB4zoYhbuSppHTa2tNi3i_HorI64uXA73chA6pwRzDfqqwTGlDlNQIi-AvWBGqMCEYsLYEVr89ydolVKsiKQcFCi2QBePUzvGZE3rs-ehd5Mds9AP2cbVPrvxo7dj7LtTdBxMm_zqL5dod7vZre_z7dPdw_p6m1sgLAfmgmNUMO-lEU5TqAotK0OU5SQUKtiCS0MCCC-t09xaYLYAqZXkxjrPl-jyMPtlumC6umz6aejmw3Jfu_1bU_pfL0Jnq5k9O7D2te_qzzjTH0N8N8N3KTRlmgDlP1h_UPY</recordid><startdate>2014</startdate><enddate>2014</enddate><creator>Nadia Ben Youssef Aicha Bouzid Noureddine Ellouze</creator><general>the Signal, Image, and Information Technology Laboratory, Department of Electrical Engineering, National Engineering School of Tunis, Tunis, Tunisia%the Department of Electrical Engineering, National Engineering School of Tunis, Tunis, Tunisia</general><scope>2RA</scope><scope>92L</scope><scope>CQIGP</scope><scope>W92</scope><scope>~WA</scope><scope>2B.</scope><scope>4A8</scope><scope>92I</scope><scope>93N</scope><scope>PSX</scope><scope>TCJ</scope></search><sort><creationdate>2014</creationdate><title>Multiscale Product for Edge Detection</title><author>Nadia Ben Youssef Aicha Bouzid Noureddine Ellouze</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c602-62dfd2142ee5a4d916b895ba07c30f87fc835a0f64e5cd93cc62c8659753acde3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>一阶导数</topic><topic>产品</topic><topic>传统方法</topic><topic>多尺度边缘检测</topic><topic>小波</topic><topic>灰度级</topic><topic>高斯函数</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nadia Ben Youssef Aicha Bouzid Noureddine Ellouze</creatorcontrib><collection>中文科技期刊数据库</collection><collection>中文科技期刊数据库-CALIS站点</collection><collection>中文科技期刊数据库-7.0平台</collection><collection>中文科技期刊数据库-工程技术</collection><collection>中文科技期刊数据库- 镜像站点</collection><collection>Wanfang Data Journals - Hong Kong</collection><collection>WANFANG Data Centre</collection><collection>Wanfang Data Journals</collection><collection>万方数据期刊 - 香港版</collection><collection>China Online Journals (COJ)</collection><collection>China Online Journals (COJ)</collection><jtitle>电子科技学刊</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nadia Ben Youssef Aicha Bouzid Noureddine Ellouze</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multiscale Product for Edge Detection</atitle><jtitle>电子科技学刊</jtitle><addtitle>Journal of Electronic Science Technology</addtitle><date>2014</date><risdate>2014</risdate><volume>12</volume><issue>1</issue><spage>112</spage><epage>115</epage><pages>112-115</pages><issn>1674-862X</issn><abstract>Many methods have been proposed to extract the most relevant areas of an image. This article explores the method of edge detection by the multiscale product （MP） of the wavelet transform. The wavelet used in this work is the first derivative of a bidimensional Gaussian function. InitiaRy, we construct the wavelet, then we present the MP approach which is applied to binary and grey levels images. This method is compared with other methods without noise and in the presence of noise. The experiment results show fhht the MP method for edge detection outPerforms conventional methods even in noisy environments.</abstract><pub>the Signal, Image, and Information Technology Laboratory, Department of Electrical Engineering, National Engineering School of Tunis, Tunis, Tunisia%the Department of Electrical Engineering, National Engineering School of Tunis, Tunis, Tunisia</pub><doi>10.3969/j.issn.1674-862X.2014.01.022</doi><tpages>4</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1674-862X |
| ispartof | 电子科技学刊, 2014, Vol.12 (1), p.112-115 |
| issn | 1674-862X |
| language | eng |
| recordid | cdi_wanfang_journals_zgdzkj_e201401022 |
| source | Alma/SFX Local Collection |
| subjects | 一阶导数 产品 传统方法 多尺度边缘检测 小波 灰度级 高斯函数 |
| title | Multiscale Product for Edge Detection |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-03T06%3A11%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-wanfang_jour_chong&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Multiscale%20Product%20for%20Edge%20Detection&rft.jtitle=%E7%94%B5%E5%AD%90%E7%A7%91%E6%8A%80%E5%AD%A6%E5%88%8A&rft.au=Nadia%20Ben%20Youssef%20Aicha%20Bouzid%20Noureddine%20Ellouze&rft.date=2014&rft.volume=12&rft.issue=1&rft.spage=112&rft.epage=115&rft.pages=112-115&rft.issn=1674-862X&rft_id=info:doi/10.3969/j.issn.1674-862X.2014.01.022&rft_dat=%3Cwanfang_jour_chong%3Ezgdzkj_e201401022%3C/wanfang_jour_chong%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_cqvip_id=49129061&rft_wanfj_id=zgdzkj_e201401022&rfr_iscdi=true |