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    KCI등재후보

    핵심 객체 추출에 기반한 비주거 시설의 화재불꽃 추출에 관한 기초 연구 = A Basic Study on the Fire Flame Extraction of Non-Residential Facilities Based on Core Object Extraction

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    https://www.riss.kr/link?id=A104313897

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    Recently, Fire watching and dangerous substances monitoring system has been being developed to enhance various fire related security. It is generally assumed that fire flame extraction plays a very important role on this monitoring system. In this study, we propose the fire flame extraction method of Non-Residential Facilities based on core object extraction in image. A core object is defined as a comparatively large object at center of the image. First of all, an input image and its decreased resolution image are segmented. Segmented regions are classified as the outer or the inner region. The outer region is adjacent to boundaries of the image and the rest is not. Then core object regions and core background regions are selected from the inner region and the outer region, respectively. Core object regions are the representative regions for the object and are selected by using the information about the region size and location. Each inner region is classified into foreground or background region by comparing its values of a color histogram intersection of the inner region against the core object region and the core background region. Finally, the extracted core object region is determined as fire flame object in the image. Through experiments, we find that to provide a basic measures can respond effectively and quickly to fire in non-residential facilities.
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    Recently, Fire watching and dangerous substances monitoring system has been being developed to enhance various fire related security. It is generally assumed that fire flame extraction plays a very important role on this monitoring system. In this stu...

    Recently, Fire watching and dangerous substances monitoring system has been being developed to enhance various fire related security. It is generally assumed that fire flame extraction plays a very important role on this monitoring system. In this study, we propose the fire flame extraction method of Non-Residential Facilities based on core object extraction in image. A core object is defined as a comparatively large object at center of the image. First of all, an input image and its decreased resolution image are segmented. Segmented regions are classified as the outer or the inner region. The outer region is adjacent to boundaries of the image and the rest is not. Then core object regions and core background regions are selected from the inner region and the outer region, respectively. Core object regions are the representative regions for the object and are selected by using the information about the region size and location. Each inner region is classified into foreground or background region by comparing its values of a color histogram intersection of the inner region against the core object region and the core background region. Finally, the extracted core object region is determined as fire flame object in the image. Through experiments, we find that to provide a basic measures can respond effectively and quickly to fire in non-residential facilities.

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    참고문헌 (Reference)

    1 국민안전처, "제1차 화재안전 기본계획" 2017

    2 한국소방안전협회, "문화재 안전관리" 2014

    3 W. Y. Ma, "NETRA: A Toolbox for Navigating Large Image Databases" 1 : 568-571, 1997

    4 Turgay Celik, "Fire Detection in Video Sequences Using a Generic Color Model" 44 (44): 147-158, 2009

    5 B.C. Ko, Cheong, "Fire Detection Based on Vision Sensor and Support Vector Machines" 41 (41): 322-329, 2009

    6 M. J Swain, "Color Indexing" 7 (7): 11-32, 1991

    7 Y.Deng, "Color Image Segmentation" 446-451, 1999

    8 Giuseppe Marbach, "An Image Processing Technique for Fire Detection in Video Images" 41 (41): 285-289, 2006

    1 국민안전처, "제1차 화재안전 기본계획" 2017

    2 한국소방안전협회, "문화재 안전관리" 2014

    3 W. Y. Ma, "NETRA: A Toolbox for Navigating Large Image Databases" 1 : 568-571, 1997

    4 Turgay Celik, "Fire Detection in Video Sequences Using a Generic Color Model" 44 (44): 147-158, 2009

    5 B.C. Ko, Cheong, "Fire Detection Based on Vision Sensor and Support Vector Machines" 41 (41): 322-329, 2009

    6 M. J Swain, "Color Indexing" 7 (7): 11-32, 1991

    7 Y.Deng, "Color Image Segmentation" 446-451, 1999

    8 Giuseppe Marbach, "An Image Processing Technique for Fire Detection in Video Images" 41 (41): 285-289, 2006

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    학술지 이력

    학술지 이력
    연월일 이력구분 이력상세 등재구분
    2027 평가 재인증평가 신청대상 (재인증)
    2021-01-01 등재 등재학술지 유지 (재인증) KCI등재
    2018-01-01 등재 등재학술지 선정 (계속평가) KCI등재
    2016-01-01 등재 등재후보학술지 선정 (신규평가) KCI등재후보
    2015-12-01 등재 등재후보 탈락 (기타)
    2014-01-01 등재 등재후보학술지 유지 (계속평가) KCI등재후보
    2013-01-01 등재 등재후보 1차 PASS (등재후보1차) KCI등재후보
    2012-01-01 등재 등재후보 1차 FAIL (기타) KCI등재후보
    2011-01-01 등재 등재후보학술지 유지 (등재후보2차) KCI등재후보
    2010-01-01 등재 등재후보 1차 PASS (등재후보1차) KCI등재후보
    2008-06-30 학회명변경 한글명 : 디지털산업정보학회 -> (사)디지털산업정보학회
    영문명 : 미등록 -> The Korea Society of Digital Industry and Information Management
    KCI등재후보
    2008-01-01 등재 등재후보학술지 선정 (신규평가) KCI등재후보
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    학술지 인용정보

    학술지 인용정보
    기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
    2016 0.46 0.46 0.37
    KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
    0.29 0.26 0.301 0.24
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