Loading…
Target Segmentation in Complex Environment Using Fractal Features
By analysis of the discrete fractal Brownian random field model, an intelligent segmentation algorithm is proposed to process targets in complex environment. Firstly, to smooth the rough background texture, four-direction gradients are extracted out for filter which would obviously reduce singular v...
Saved in:
Main Authors: | , , |
---|---|
Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | |
---|---|
cites | |
container_end_page | 83 |
container_issue | |
container_start_page | 79 |
container_title | |
container_volume | 1 |
creator | Ding Su Qiheng Zhang Shenghua Xie |
description | By analysis of the discrete fractal Brownian random field model, an intelligent segmentation algorithm is proposed to process targets in complex environment. Firstly, to smooth the rough background texture, four-direction gradients are extracted out for filter which would obviously reduce singular values with variable gray intensity distribution. Secondly, a new fractal parameter, named fractal modulation degree, is computed out to highlight immanent diversities of target and background. Then, passing through three-layer BP NN, multi-features are trained to obtain rational weight values and perform pattern recognition. Eventually, the contour of target is segmented out. Abundant experiments support the scheme's satisfying validity and reliability |
doi_str_mv | 10.1109/COGINF.2006.365680 |
format | conference_proceeding |
fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_4216395</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>4216395</ieee_id><sourcerecordid>4216395</sourcerecordid><originalsourceid>FETCH-LOGICAL-i175t-a3ccaae3ebb8c6dc84c830f117c758ad5bc14047fd15794cdb0b0c747bfffebb3</originalsourceid><addsrcrecordid>eNotjs1KxDAYRQMiKGNfQDd5gdak-e1yKFMVBl04sx6S9EuJtOmQRtG3t4PezV1czuUgdE9JRSlpHtu3p5fXrqoJkRWTQmpyhYpGacprzglXorlBxbJ8kDWsYUqKW7Q9mDRAxu8wTBCzyWGOOETcztN5hG-8i18hzfGy4eMS4oC7ZFw2I-7A5M8Eyx269mZcoPjvDTp2u0P7XO5XnXa7LwNVIpeGOWcMMLBWO9k7zZ1mxFOqnBLa9MI6epH0PRWq4a63xBKnuLLe-xViG_Tw9xsA4HROYTLp58RrKlkj2C-x-Eq0</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Target Segmentation in Complex Environment Using Fractal Features</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Ding Su ; Qiheng Zhang ; Shenghua Xie</creator><creatorcontrib>Ding Su ; Qiheng Zhang ; Shenghua Xie</creatorcontrib><description>By analysis of the discrete fractal Brownian random field model, an intelligent segmentation algorithm is proposed to process targets in complex environment. Firstly, to smooth the rough background texture, four-direction gradients are extracted out for filter which would obviously reduce singular values with variable gray intensity distribution. Secondly, a new fractal parameter, named fractal modulation degree, is computed out to highlight immanent diversities of target and background. Then, passing through three-layer BP NN, multi-features are trained to obtain rational weight values and perform pattern recognition. Eventually, the contour of target is segmented out. Abundant experiments support the scheme's satisfying validity and reliability</description><identifier>ISBN: 9781424404759</identifier><identifier>ISBN: 1424404754</identifier><identifier>DOI: 10.1109/COGINF.2006.365680</identifier><language>eng</language><publisher>IEEE</publisher><subject>Algorithm design and analysis ; BP NN ; Content addressable storage ; Equations ; Fractal ; Fractals ; Mathematical model ; Multi-features ; Neural networks ; Optical control ; Optical filters ; Pattern recognition ; Robustness ; Segmentation ; Smooth</subject><ispartof>2006 5th IEEE International Conference on Cognitive Informatics, 2006, Vol.1, p.79-83</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4216395$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2051,27904,54899</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4216395$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Ding Su</creatorcontrib><creatorcontrib>Qiheng Zhang</creatorcontrib><creatorcontrib>Shenghua Xie</creatorcontrib><title>Target Segmentation in Complex Environment Using Fractal Features</title><title>2006 5th IEEE International Conference on Cognitive Informatics</title><addtitle>COGINF</addtitle><description>By analysis of the discrete fractal Brownian random field model, an intelligent segmentation algorithm is proposed to process targets in complex environment. Firstly, to smooth the rough background texture, four-direction gradients are extracted out for filter which would obviously reduce singular values with variable gray intensity distribution. Secondly, a new fractal parameter, named fractal modulation degree, is computed out to highlight immanent diversities of target and background. Then, passing through three-layer BP NN, multi-features are trained to obtain rational weight values and perform pattern recognition. Eventually, the contour of target is segmented out. Abundant experiments support the scheme's satisfying validity and reliability</description><subject>Algorithm design and analysis</subject><subject>BP NN</subject><subject>Content addressable storage</subject><subject>Equations</subject><subject>Fractal</subject><subject>Fractals</subject><subject>Mathematical model</subject><subject>Multi-features</subject><subject>Neural networks</subject><subject>Optical control</subject><subject>Optical filters</subject><subject>Pattern recognition</subject><subject>Robustness</subject><subject>Segmentation</subject><subject>Smooth</subject><isbn>9781424404759</isbn><isbn>1424404754</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2006</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotjs1KxDAYRQMiKGNfQDd5gdak-e1yKFMVBl04sx6S9EuJtOmQRtG3t4PezV1czuUgdE9JRSlpHtu3p5fXrqoJkRWTQmpyhYpGacprzglXorlBxbJ8kDWsYUqKW7Q9mDRAxu8wTBCzyWGOOETcztN5hG-8i18hzfGy4eMS4oC7ZFw2I-7A5M8Eyx269mZcoPjvDTp2u0P7XO5XnXa7LwNVIpeGOWcMMLBWO9k7zZ1mxFOqnBLa9MI6epH0PRWq4a63xBKnuLLe-xViG_Tw9xsA4HROYTLp58RrKlkj2C-x-Eq0</recordid><startdate>200607</startdate><enddate>200607</enddate><creator>Ding Su</creator><creator>Qiheng Zhang</creator><creator>Shenghua Xie</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200607</creationdate><title>Target Segmentation in Complex Environment Using Fractal Features</title><author>Ding Su ; Qiheng Zhang ; Shenghua Xie</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-a3ccaae3ebb8c6dc84c830f117c758ad5bc14047fd15794cdb0b0c747bfffebb3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Algorithm design and analysis</topic><topic>BP NN</topic><topic>Content addressable storage</topic><topic>Equations</topic><topic>Fractal</topic><topic>Fractals</topic><topic>Mathematical model</topic><topic>Multi-features</topic><topic>Neural networks</topic><topic>Optical control</topic><topic>Optical filters</topic><topic>Pattern recognition</topic><topic>Robustness</topic><topic>Segmentation</topic><topic>Smooth</topic><toplevel>online_resources</toplevel><creatorcontrib>Ding Su</creatorcontrib><creatorcontrib>Qiheng Zhang</creatorcontrib><creatorcontrib>Shenghua Xie</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 Xplore (Online service)</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>Ding Su</au><au>Qiheng Zhang</au><au>Shenghua Xie</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Target Segmentation in Complex Environment Using Fractal Features</atitle><btitle>2006 5th IEEE International Conference on Cognitive Informatics</btitle><stitle>COGINF</stitle><date>2006-07</date><risdate>2006</risdate><volume>1</volume><spage>79</spage><epage>83</epage><pages>79-83</pages><isbn>9781424404759</isbn><isbn>1424404754</isbn><abstract>By analysis of the discrete fractal Brownian random field model, an intelligent segmentation algorithm is proposed to process targets in complex environment. Firstly, to smooth the rough background texture, four-direction gradients are extracted out for filter which would obviously reduce singular values with variable gray intensity distribution. Secondly, a new fractal parameter, named fractal modulation degree, is computed out to highlight immanent diversities of target and background. Then, passing through three-layer BP NN, multi-features are trained to obtain rational weight values and perform pattern recognition. Eventually, the contour of target is segmented out. Abundant experiments support the scheme's satisfying validity and reliability</abstract><pub>IEEE</pub><doi>10.1109/COGINF.2006.365680</doi><tpages>5</tpages></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISBN: 9781424404759 |
ispartof | 2006 5th IEEE International Conference on Cognitive Informatics, 2006, Vol.1, p.79-83 |
issn | |
language | eng |
recordid | cdi_ieee_primary_4216395 |
source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Algorithm design and analysis BP NN Content addressable storage Equations Fractal Fractals Mathematical model Multi-features Neural networks Optical control Optical filters Pattern recognition Robustness Segmentation Smooth |
title | Target Segmentation in Complex Environment Using Fractal Features |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-22T22%3A38%3A43IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Target%20Segmentation%20in%20Complex%20Environment%20Using%20Fractal%20Features&rft.btitle=2006%205th%20IEEE%20International%20Conference%20on%20Cognitive%20Informatics&rft.au=Ding%20Su&rft.date=2006-07&rft.volume=1&rft.spage=79&rft.epage=83&rft.pages=79-83&rft.isbn=9781424404759&rft.isbn_list=1424404754&rft_id=info:doi/10.1109/COGINF.2006.365680&rft_dat=%3Cieee_6IE%3E4216395%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i175t-a3ccaae3ebb8c6dc84c830f117c758ad5bc14047fd15794cdb0b0c747bfffebb3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=4216395&rfr_iscdi=true |