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<ArticleSet>
  <Article>
    <Journal>
      <PublisherName>IJIRCSTJournal</PublisherName>
      <JournalTitle>International Journal of Innovative Research in Computer Science and Technology</JournalTitle>
      <PISSN>I</PISSN>
      <EISSN>S</EISSN>
      <Volume-Issue>Volume 10 Issue 2</Volume-Issue>
      <PartNumber/>
      <IssueTopic>Management</IssueTopic>
      <IssueLanguage>English</IssueLanguage>
      <Season>March - April 2022</Season>
      <SpecialIssue>N</SpecialIssue>
      <SupplementaryIssue>N</SupplementaryIssue>
      <IssueOA>Y</IssueOA>
      <PubDate>
        <Year>2022</Year>
        <Month>06</Month>
        <Day>01</Day>
      </PubDate>
      <ArticleType>Computer Sciences</ArticleType>
      <ArticleTitle>Image Prrocessing With LBP</ArticleTitle>
      <SubTitle/>
      <ArticleLanguage>English</ArticleLanguage>
      <ArticleOA>Y</ArticleOA>
      <FirstPage>490</FirstPage>
      <LastPage>496</LastPage>
      <AuthorList>
        <Author>
          <FirstName>Niharika Vikesh Agarwal</FirstName>          
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>Y</CorrespondingAuthor>
          <ORCID/>
                      <FirstName>Payal Parekh</FirstName>          
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>N</CorrespondingAuthor>
          <ORCID/>
           
        </Author>
      </AuthorList>
      <DOI>https://doi.org/10.55524/ijircst.2022.10.2.98</DOI>
      <Abstract>LBP is a simple yet effective pattern operator which recognizes pixels in pictures by thresholding every pixel&amp;#39;s neighborhood as well as treating the result as a binary integers. Image classification is important in a range of computer applications because it divides pictures into sections based on information retrieved from the image. In the literature, several methods for extracting characteristics from photos have been presented. Patterns LBP is among the most often utilized approaches because to its computational simplicity. The authors present the LBP pixel methods in this article, which includes a variety of LBP as well as related publications. It preserves the bulk of the picture&amp;#39;s essential visual elements due to its invariance to differences in light and its dependability in image classification. LBP also has the benefit of creating an 8-bit descriptor for every pixel as well as being sensitive to picture rotation. &amp;nbsp;The main objective of this paper is that, it would be able to provide maximum accuracy in image Processing Technique. Image processing&amp;#39;s future potential include exploring the sky for other sentient species in space.</Abstract>
      <AbstractLanguage>English</AbstractLanguage>
      <Keywords>Diagonal Intersection, Feature Extraction, Image Descriptor, Image Classification, LBP.</Keywords>
      <URLs>
        <Abstract>https://ijircst.org/abstract.php?article_id=936</Abstract>
      </URLs>      
    </Journal>
  </Article>
</ArticleSet>