Fast and Robust Underwater Obstacle Detection in Acoustic Vision

Sonar is a vital instrument for underwater detection. BlueView(BV) as an acoustic vision sensor is subject to structural noise during detection. This phenomenon has a negative impact on the detection and image restoration of sonar. In this paper, we propose an improved Bayes estimation method for ac...

Full description

Saved in:
Bibliographic Details
Main Authors: Liu, Hengrui, Chen, Deshan, Zhang, Di, Zhou, Peng
Format: Conference Proceeding
Language:English
Subjects:
Acoustics
Estimation
Image edge detection
information fusion
Instruments
Object detection
robust detection
Sonar
structural noise
underwater obstacles
Vision sensors
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 6
container_issue
container_start_page 1
container_title
container_volume
creator Liu, Hengrui
Chen, Deshan
Zhang, Di
Zhou, Peng
description Sonar is a vital instrument for underwater detection. BlueView(BV) as an acoustic vision sensor is subject to structural noise during detection. This phenomenon has a negative impact on the detection and image restoration of sonar. In this paper, we propose an improved Bayes estimation method for acoustic vision object detection in the BV forward looking sonar images. The method is based on Gaussian mixture model and to represent background prior probability model for each pixel. The conditional probability model construction via an improved sigmoid model. As verified experimentally, the proposed method shows a fast yet robust result.
doi_str_mv 10.1109/ICSSE50014.2020.9219258
format conference_proceeding
fullrecord <record><control><sourceid>ieee_CHZPO</sourceid><recordid>TN_cdi_ieee_primary_9219258</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9219258</ieee_id><sourcerecordid>9219258</sourcerecordid><originalsourceid>FETCH-LOGICAL-i118t-e11387d874ecea4d81b230909c38b2d02e491495a134285113f353217b58902d3</originalsourceid><addsrcrecordid>eNotT8FKAzEUjIJgqfsFHswP7PreS2KSm2VttVAoWOu1ZDevEKm7shsR_94Fe5phZhhmhLhDqBDB36_r3W5pAFBXBASVJ_Rk3IUovHVoyaHxD2AvxYwUmRIm81oU4_gBAIoQrbcz8bgKY5ahi_K1b74nuu8iDz8h8yC3zZhDe2L5xJnbnPpOpk4u2n7KpVa-p3GSbsTVMZxGLs44F_vV8q1-KTfb53W92JQJ0eWSEZWz0VnNLQcdHTakwINvlWsoArH2qL0JqDQ5M6WPykwrbWOcB4pqLm7_exMzH76G9BmG38P5s_oDYARJkQ</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Fast and Robust Underwater Obstacle Detection in Acoustic Vision</title><source>IEEE Xplore All Conference Series</source><creator>Liu, Hengrui ; Chen, Deshan ; Zhang, Di ; Zhou, Peng</creator><creatorcontrib>Liu, Hengrui ; Chen, Deshan ; Zhang, Di ; Zhou, Peng</creatorcontrib><description>Sonar is a vital instrument for underwater detection. BlueView(BV) as an acoustic vision sensor is subject to structural noise during detection. This phenomenon has a negative impact on the detection and image restoration of sonar. In this paper, we propose an improved Bayes estimation method for acoustic vision object detection in the BV forward looking sonar images. The method is based on Gaussian mixture model and to represent background prior probability model for each pixel. The conditional probability model construction via an improved sigmoid model. As verified experimentally, the proposed method shows a fast yet robust result.</description><identifier>EISSN: 2325-0925</identifier><identifier>EISBN: 9781728159607</identifier><identifier>EISBN: 1728159601</identifier><identifier>DOI: 10.1109/ICSSE50014.2020.9219258</identifier><language>eng</language><publisher>IEEE</publisher><subject>Acoustics ; Estimation ; Image edge detection ; information fusion ; Instruments ; Object detection ; robust detection ; Sonar ; structural noise ; underwater obstacles ; Vision sensors</subject><ispartof>2020 International Conference on System Science and Engineering (ICSSE), 2020, p.1-6</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/9219258$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,27925,54555,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9219258$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Liu, Hengrui</creatorcontrib><creatorcontrib>Chen, Deshan</creatorcontrib><creatorcontrib>Zhang, Di</creatorcontrib><creatorcontrib>Zhou, Peng</creatorcontrib><title>Fast and Robust Underwater Obstacle Detection in Acoustic Vision</title><title>2020 International Conference on System Science and Engineering (ICSSE)</title><addtitle>ICSSE</addtitle><description>Sonar is a vital instrument for underwater detection. BlueView(BV) as an acoustic vision sensor is subject to structural noise during detection. This phenomenon has a negative impact on the detection and image restoration of sonar. In this paper, we propose an improved Bayes estimation method for acoustic vision object detection in the BV forward looking sonar images. The method is based on Gaussian mixture model and to represent background prior probability model for each pixel. The conditional probability model construction via an improved sigmoid model. As verified experimentally, the proposed method shows a fast yet robust result.</description><subject>Acoustics</subject><subject>Estimation</subject><subject>Image edge detection</subject><subject>information fusion</subject><subject>Instruments</subject><subject>Object detection</subject><subject>robust detection</subject><subject>Sonar</subject><subject>structural noise</subject><subject>underwater obstacles</subject><subject>Vision sensors</subject><issn>2325-0925</issn><isbn>9781728159607</isbn><isbn>1728159601</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2020</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotT8FKAzEUjIJgqfsFHswP7PreS2KSm2VttVAoWOu1ZDevEKm7shsR_94Fe5phZhhmhLhDqBDB36_r3W5pAFBXBASVJ_Rk3IUovHVoyaHxD2AvxYwUmRIm81oU4_gBAIoQrbcz8bgKY5ahi_K1b74nuu8iDz8h8yC3zZhDe2L5xJnbnPpOpk4u2n7KpVa-p3GSbsTVMZxGLs44F_vV8q1-KTfb53W92JQJ0eWSEZWz0VnNLQcdHTakwINvlWsoArH2qL0JqDQ5M6WPykwrbWOcB4pqLm7_exMzH76G9BmG38P5s_oDYARJkQ</recordid><startdate>202008</startdate><enddate>202008</enddate><creator>Liu, Hengrui</creator><creator>Chen, Deshan</creator><creator>Zhang, Di</creator><creator>Zhou, Peng</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>202008</creationdate><title>Fast and Robust Underwater Obstacle Detection in Acoustic Vision</title><author>Liu, Hengrui ; Chen, Deshan ; Zhang, Di ; Zhou, Peng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i118t-e11387d874ecea4d81b230909c38b2d02e491495a134285113f353217b58902d3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Acoustics</topic><topic>Estimation</topic><topic>Image edge detection</topic><topic>information fusion</topic><topic>Instruments</topic><topic>Object detection</topic><topic>robust detection</topic><topic>Sonar</topic><topic>structural noise</topic><topic>underwater obstacles</topic><topic>Vision sensors</topic><toplevel>online_resources</toplevel><creatorcontrib>Liu, Hengrui</creatorcontrib><creatorcontrib>Chen, Deshan</creatorcontrib><creatorcontrib>Zhang, Di</creatorcontrib><creatorcontrib>Zhou, Peng</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</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>Liu, Hengrui</au><au>Chen, Deshan</au><au>Zhang, Di</au><au>Zhou, Peng</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Fast and Robust Underwater Obstacle Detection in Acoustic Vision</atitle><btitle>2020 International Conference on System Science and Engineering (ICSSE)</btitle><stitle>ICSSE</stitle><date>2020-08</date><risdate>2020</risdate><spage>1</spage><epage>6</epage><pages>1-6</pages><eissn>2325-0925</eissn><eisbn>9781728159607</eisbn><eisbn>1728159601</eisbn><abstract>Sonar is a vital instrument for underwater detection. BlueView(BV) as an acoustic vision sensor is subject to structural noise during detection. This phenomenon has a negative impact on the detection and image restoration of sonar. In this paper, we propose an improved Bayes estimation method for acoustic vision object detection in the BV forward looking sonar images. The method is based on Gaussian mixture model and to represent background prior probability model for each pixel. The conditional probability model construction via an improved sigmoid model. As verified experimentally, the proposed method shows a fast yet robust result.</abstract><pub>IEEE</pub><doi>10.1109/ICSSE50014.2020.9219258</doi><tpages>6</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier EISSN: 2325-0925
ispartof 2020 International Conference on System Science and Engineering (ICSSE), 2020, p.1-6
issn 2325-0925
language eng
recordid cdi_ieee_primary_9219258
source IEEE Xplore All Conference Series
subjects Acoustics
Estimation
Image edge detection
information fusion
Instruments
Object detection
robust detection
Sonar
structural noise
underwater obstacles
Vision sensors
title Fast and Robust Underwater Obstacle Detection in Acoustic Vision
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-02T00%3A14%3A37IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_CHZPO&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Fast%20and%20Robust%20Underwater%20Obstacle%20Detection%20in%20Acoustic%20Vision&rft.btitle=2020%20International%20Conference%20on%20System%20Science%20and%20Engineering%20(ICSSE)&rft.au=Liu,%20Hengrui&rft.date=2020-08&rft.spage=1&rft.epage=6&rft.pages=1-6&rft.eissn=2325-0925&rft_id=info:doi/10.1109/ICSSE50014.2020.9219258&rft.eisbn=9781728159607&rft.eisbn_list=1728159601&rft_dat=%3Cieee_CHZPO%3E9219258%3C/ieee_CHZPO%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i118t-e11387d874ecea4d81b230909c38b2d02e491495a134285113f353217b58902d3%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=9219258&rfr_iscdi=true