Edge-Enhancing of Color Segmented Images
This paper introduces a new approach to edge-preserving smoothing of color segmented images. It is well suited for an efficient reduction of the texture contours in colored images that is an essential step in applications such as image classification or image retrieval. The algorithm reduces the art...
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creator | Kourgli, A. Oukil, Y. |
description | This paper introduces a new approach to edge-preserving smoothing of color segmented images. It is well suited for an efficient reduction of the texture contours in colored images that is an essential step in applications such as image classification or image retrieval. The algorithm reduces the artifacts in the homogeneous areas, but preserves all image structures like edges or corners. Our procedure uses mean-shift algorithm to obtain a colored segmented images. The filtering algorithm is not only applicable to color images segmented using mean-shift, but can be applied to any segmented images too. It is formalized through the definition of a morphological window and a homogeneity measure on this window. The adaptive filter presented here tries to overcome some of the disadvantages of existing smoothing filters and is conceived as an extension of the morphological profiles filtering. The experimental results over Berkeley database images show that the proposed method is well suited for textured image scenes. |
doi_str_mv | 10.1109/SITIS.2012.35 |
format | Conference Proceeding |
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It is well suited for an efficient reduction of the texture contours in colored images that is an essential step in applications such as image classification or image retrieval. The algorithm reduces the artifacts in the homogeneous areas, but preserves all image structures like edges or corners. Our procedure uses mean-shift algorithm to obtain a colored segmented images. The filtering algorithm is not only applicable to color images segmented using mean-shift, but can be applied to any segmented images too. It is formalized through the definition of a morphological window and a homogeneity measure on this window. The adaptive filter presented here tries to overcome some of the disadvantages of existing smoothing filters and is conceived as an extension of the morphological profiles filtering. 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It is well suited for an efficient reduction of the texture contours in colored images that is an essential step in applications such as image classification or image retrieval. The algorithm reduces the artifacts in the homogeneous areas, but preserves all image structures like edges or corners. Our procedure uses mean-shift algorithm to obtain a colored segmented images. The filtering algorithm is not only applicable to color images segmented using mean-shift, but can be applied to any segmented images too. It is formalized through the definition of a morphological window and a homogeneity measure on this window. The adaptive filter presented here tries to overcome some of the disadvantages of existing smoothing filters and is conceived as an extension of the morphological profiles filtering. The experimental results over Berkeley database images show that the proposed method is well suited for textured image scenes.</description><subject>Adaptive filters</subject><subject>color images</subject><subject>edge-preserving smoothing filter</subject><subject>Filtering</subject><subject>Filtering algorithms</subject><subject>Image color analysis</subject><subject>Image edge detection</subject><subject>Image segmentation</subject><subject>segmentation</subject><subject>Smoothing methods</subject><isbn>1467351520</isbn><isbn>9781467351522</isbn><isbn>9780769549118</isbn><isbn>076954911X</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotzDFPg0AUAOAzxkRtGZ1cGF3A9-6497jREFSSJg60c3O9eyCmgIEu_nsHnb7tU-oBIUcE99w2-6bNNaDOjb1SieMSmJwtHGJ5re6xIDYWrYZblazrFwAgGAtU3KmnOvaS1dOnn8Iw9encpdV8npe0lX6U6SIxbUbfy7pVN50_r5L8u1GH13pfvWe7j7emetllA7K9ZMFzcIzORMPcSSxjsBwN6PJEJ49EUAAQhS5QYNAQrTeeIhSdYyHPZqMe_95BRI7fyzD65edIxllwaH4B0IU_-g</recordid><startdate>201211</startdate><enddate>201211</enddate><creator>Kourgli, A.</creator><creator>Oukil, Y.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201211</creationdate><title>Edge-Enhancing of Color Segmented Images</title><author>Kourgli, A. ; Oukil, Y.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-ca7c97193d377fed8dc57d3028b6ba166040066cfc6c7020d5a3a6d04f97e6a73</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Adaptive filters</topic><topic>color images</topic><topic>edge-preserving smoothing filter</topic><topic>Filtering</topic><topic>Filtering algorithms</topic><topic>Image color analysis</topic><topic>Image edge detection</topic><topic>Image segmentation</topic><topic>segmentation</topic><topic>Smoothing methods</topic><toplevel>online_resources</toplevel><creatorcontrib>Kourgli, A.</creatorcontrib><creatorcontrib>Oukil, Y.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kourgli, A.</au><au>Oukil, Y.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Edge-Enhancing of Color Segmented Images</atitle><btitle>2012 Eighth International Conference on Signal Image Technology and Internet Based Systems</btitle><stitle>sitis</stitle><date>2012-11</date><risdate>2012</risdate><spage>168</spage><epage>173</epage><pages>168-173</pages><isbn>1467351520</isbn><isbn>9781467351522</isbn><eisbn>9780769549118</eisbn><eisbn>076954911X</eisbn><coden>IEEPAD</coden><abstract>This paper introduces a new approach to edge-preserving smoothing of color segmented images. It is well suited for an efficient reduction of the texture contours in colored images that is an essential step in applications such as image classification or image retrieval. The algorithm reduces the artifacts in the homogeneous areas, but preserves all image structures like edges or corners. Our procedure uses mean-shift algorithm to obtain a colored segmented images. The filtering algorithm is not only applicable to color images segmented using mean-shift, but can be applied to any segmented images too. It is formalized through the definition of a morphological window and a homogeneity measure on this window. The adaptive filter presented here tries to overcome some of the disadvantages of existing smoothing filters and is conceived as an extension of the morphological profiles filtering. The experimental results over Berkeley database images show that the proposed method is well suited for textured image scenes.</abstract><pub>IEEE</pub><doi>10.1109/SITIS.2012.35</doi><tpages>6</tpages></addata></record> |
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subjects | Adaptive filters color images edge-preserving smoothing filter Filtering Filtering algorithms Image color analysis Image edge detection Image segmentation segmentation Smoothing methods |
title | Edge-Enhancing of Color Segmented Images |
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