Survey of Texture Segmentation, Classification, and Synthesis Methods
This report reviews the literature in the areas of image texture segmentation, classification, and synthesis methods. The approaches to these areas are grouped into areas of fractal, spline, neural networks, modeling, and stochastic methods. An immense amount of literature was reviewed, and techniqu...
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creator | Bourgeois, Brian S Walker, Charles L |
description | This report reviews the literature in the areas of image texture segmentation, classification, and synthesis methods. The approaches to these areas are grouped into areas of fractal, spline, neural networks, modeling, and stochastic methods. An immense amount of literature was reviewed, and techniques with the most merit are presented. From the review it appears that no single approach provides a robust texture analysis methodology without requiring overwhelming complexity. It seems that the best approach to the problem may be to use a variety of these methods in the simplest and most computationally economic forms. |
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The approaches to these areas are grouped into areas of fractal, spline, neural networks, modeling, and stochastic methods. An immense amount of literature was reviewed, and techniques with the most merit are presented. From the review it appears that no single approach provides a robust texture analysis methodology without requiring overwhelming complexity. It seems that the best approach to the problem may be to use a variety of these methods in the simplest and most computationally economic forms.</description><language>eng</language><subject>Acoustic Detection and Detectors ; ACOUSTIC IMAGES ; APPROACH ; BATHYMETRY ; CLASSIFICATION ; CLOUDS ; ECONOMICS ; FRACTALS ; HYDROGRAPHY ; IMAGE PROCESSING ; METHODOLOGY ; NETWORKS ; NEURAL NETS ; Numerical Mathematics ; OPTICAL PROPERTIES ; SIDE LOOKING SONAR ; SONAR IMAGES ; SPLINES ; SYNTHESIS ; TERRAIN ; TEXTURE ; TIDES</subject><creationdate>1992</creationdate><rights>Approved for public release; distribution is unlimited.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,776,881,27544,27545</link.rule.ids><linktorsrc>$$Uhttps://apps.dtic.mil/sti/citations/ADA252623$$EView_record_in_DTIC$$FView_record_in_$$GDTIC$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Bourgeois, Brian S</creatorcontrib><creatorcontrib>Walker, Charles L</creatorcontrib><creatorcontrib>NAVAL OCEANOGRAPHIC AND ATMOSPHERIC RESEARCH LAB STENNIS SPACE CENTER MS</creatorcontrib><title>Survey of Texture Segmentation, Classification, and Synthesis Methods</title><description>This report reviews the literature in the areas of image texture segmentation, classification, and synthesis methods. The approaches to these areas are grouped into areas of fractal, spline, neural networks, modeling, and stochastic methods. An immense amount of literature was reviewed, and techniques with the most merit are presented. From the review it appears that no single approach provides a robust texture analysis methodology without requiring overwhelming complexity. It seems that the best approach to the problem may be to use a variety of these methods in the simplest and most computationally economic forms.</description><subject>Acoustic Detection and Detectors</subject><subject>ACOUSTIC IMAGES</subject><subject>APPROACH</subject><subject>BATHYMETRY</subject><subject>CLASSIFICATION</subject><subject>CLOUDS</subject><subject>ECONOMICS</subject><subject>FRACTALS</subject><subject>HYDROGRAPHY</subject><subject>IMAGE PROCESSING</subject><subject>METHODOLOGY</subject><subject>NETWORKS</subject><subject>NEURAL NETS</subject><subject>Numerical Mathematics</subject><subject>OPTICAL PROPERTIES</subject><subject>SIDE LOOKING SONAR</subject><subject>SONAR IMAGES</subject><subject>SPLINES</subject><subject>SYNTHESIS</subject><subject>TERRAIN</subject><subject>TEXTURE</subject><subject>TIDES</subject><fulltext>true</fulltext><rsrctype>report</rsrctype><creationdate>1992</creationdate><recordtype>report</recordtype><sourceid>1RU</sourceid><recordid>eNrjZHANLi0qS61UyE9TCEmtKCktSlUITk3PTc0rSSzJzM_TUXDOSSwuzkzLTIbyE_NSFIIr80oyUoszixV8U0sy8lOKeRhY0xJzilN5oTQ3g4yba4izh25KSWZyfHFJZl5qSbyji6ORqZGZkbExAWkA8sowRw</recordid><startdate>199201</startdate><enddate>199201</enddate><creator>Bourgeois, Brian S</creator><creator>Walker, Charles L</creator><scope>1RU</scope><scope>BHM</scope></search><sort><creationdate>199201</creationdate><title>Survey of Texture Segmentation, Classification, and Synthesis Methods</title><author>Bourgeois, Brian S ; Walker, Charles L</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-dtic_stinet_ADA2526233</frbrgroupid><rsrctype>reports</rsrctype><prefilter>reports</prefilter><language>eng</language><creationdate>1992</creationdate><topic>Acoustic Detection and Detectors</topic><topic>ACOUSTIC IMAGES</topic><topic>APPROACH</topic><topic>BATHYMETRY</topic><topic>CLASSIFICATION</topic><topic>CLOUDS</topic><topic>ECONOMICS</topic><topic>FRACTALS</topic><topic>HYDROGRAPHY</topic><topic>IMAGE PROCESSING</topic><topic>METHODOLOGY</topic><topic>NETWORKS</topic><topic>NEURAL NETS</topic><topic>Numerical Mathematics</topic><topic>OPTICAL PROPERTIES</topic><topic>SIDE LOOKING SONAR</topic><topic>SONAR IMAGES</topic><topic>SPLINES</topic><topic>SYNTHESIS</topic><topic>TERRAIN</topic><topic>TEXTURE</topic><topic>TIDES</topic><toplevel>online_resources</toplevel><creatorcontrib>Bourgeois, Brian S</creatorcontrib><creatorcontrib>Walker, Charles L</creatorcontrib><creatorcontrib>NAVAL OCEANOGRAPHIC AND ATMOSPHERIC RESEARCH LAB STENNIS SPACE CENTER MS</creatorcontrib><collection>DTIC Technical Reports</collection><collection>DTIC STINET</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Bourgeois, Brian S</au><au>Walker, Charles L</au><aucorp>NAVAL OCEANOGRAPHIC AND ATMOSPHERIC RESEARCH LAB STENNIS SPACE CENTER MS</aucorp><format>book</format><genre>unknown</genre><ristype>RPRT</ristype><btitle>Survey of Texture Segmentation, Classification, and Synthesis Methods</btitle><date>1992-01</date><risdate>1992</risdate><abstract>This report reviews the literature in the areas of image texture segmentation, classification, and synthesis methods. The approaches to these areas are grouped into areas of fractal, spline, neural networks, modeling, and stochastic methods. An immense amount of literature was reviewed, and techniques with the most merit are presented. From the review it appears that no single approach provides a robust texture analysis methodology without requiring overwhelming complexity. It seems that the best approach to the problem may be to use a variety of these methods in the simplest and most computationally economic forms.</abstract><oa>free_for_read</oa></addata></record> |
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language | eng |
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source | DTIC Technical Reports |
subjects | Acoustic Detection and Detectors ACOUSTIC IMAGES APPROACH BATHYMETRY CLASSIFICATION CLOUDS ECONOMICS FRACTALS HYDROGRAPHY IMAGE PROCESSING METHODOLOGY NETWORKS NEURAL NETS Numerical Mathematics OPTICAL PROPERTIES SIDE LOOKING SONAR SONAR IMAGES SPLINES SYNTHESIS TERRAIN TEXTURE TIDES |
title | Survey of Texture Segmentation, Classification, and Synthesis Methods |
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