September 30, 2020 Journal article Open Access

R. Sandhiya; Santhoshini Arulvallal; Lakshmi Shree. B; D. Dhina

DataCite XML Export

<?xml version='1.0' encoding='utf-8'?>
<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd">
  <identifier identifierType="URL">https://zenodo.org/record/5853957</identifier>
  <creators>
    <creator>
      <creatorName>R. Sandhiya</creatorName>
      <affiliation>Department of Biomedical Engineering, AVIT, Chennai,  India</affiliation>
    </creator>
    <creator>
      <creatorName>Santhoshini Arulvallal</creatorName>
      <affiliation>Department of Biomedical Engineering, AVIT,  Chennai, India.</affiliation>
    </creator>
    <creator>
      <creatorName>Lakshmi Shree. B</creatorName>
      <affiliation>Department of Biomedical Engineering, AVIT,  Chennai, India.</affiliation>
    </creator>
    <creator>
      <creatorName>D. Dhina</creatorName>
      <affiliation>Department of Biomedical Engineering, AVIT,  Chennai, India.</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Fire Recognition based on Image Processing using  Raspberry pi</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>GMM, GPIO, GPS, Open CV, RPi, SoC</subject>
    <subject subjectScheme="issn">2278-3075</subject>
    <subject subjectScheme="handle">100.1/ijitee.J76060891020</subject>
  </subjects>
  <contributors>
    <contributor contributorType="Sponsor">
      <contributorName>Blue Eyes Intelligence Engineering  and Sciences Publication(BEIESP)</contributorName>
      <affiliation>Publisher</affiliation>
    </contributor>
  </contributors>
  <dates>
    <date dateType="Issued">2020-09-30</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5853957</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="ISSN" relationType="IsCitedBy" resourceTypeGeneral="JournalArticle">2278-3075</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.35940/ijitee.J7606.0991120</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Fire is a procedure of ignition that brings calamity. It becomes unsafe when fire loses control and spreads out. The fire detection becomes more and more important with the rapid development of image and video processing, the fire detection technology based on video processing is becoming the focal point of some research due to its advantages of high intuitive, speed and anti-jamming capability. This method uses colour and motion information extracted from video sequences to detect fire. It can work both indoor and outdoor environments. Moreover, it detects fire at the beginning of the burning process. The method performs the region growing segmentation to identify colour pixels in the scene and then identify moving pixels based on the ratio of height and width of suspected fire region. This method can get low false alarm rate by eliminating the fire-like colours because it just needs a fire pixel as the seed pixel. .&lt;/p&gt;</description>
  </descriptions>
</resource>