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  <titleInfo>
    <title>Real time face detection system</title>
  </titleInfo>
  <titleInfo type="alternative">
    <title>Real time face detection system</title>
  </titleInfo>
  <name type="personal">
    <namePart>Amy Safrina Mohd Ali</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <typeOfResource>text</typeOfResource>
  <genre authority="marc">theses</genre>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">my</placeTerm>
    </place>
    <place>
      <placeTerm type="text">Kuantan, Pahang</placeTerm>
    </place>
    <publisher>UMP</publisher>
    <dateIssued>2009</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">print</form>
    <form authority="gmd">electronic resource</form>
    <extent>57 p. : ill. (some col.) ; 30 cm. + 1 computer disc</extent>
  </physicalDescription>
  <abstract>䚐ÔﴈÔ  face detection system  is a computer application  for automatically detecting a   human face from digital  image or video frame from a video source. This project  is used   web  camera  to  capture  the  image  in  real  time.  This  face  detection  system  used Haar   Classifier method  to detect  face and extract human  face. Haar Classifier  technique can   detect  human  face  very  face  and  can  achieve  high  detection  accuracy. This  system  is   build using Visual Studio C++ 8 edition and Opencv to setup the interface between web   camera and computer. This system also used Graphical User  Interface  (GUI)  to design   client window. Besides  that this system used Graphic Device Interface (GDI)  library  to   select  the  interest  region. This system can detect  the  face  image and can automatically   save the  image. This system can be applied  in the banking system to reduce the number   of forgery.  </abstract>
  <targetAudience authority="marctarget">specialized</targetAudience>
  <note type="statement of responsibility">Amy Safrina Mohd Ali</note>
  <note>Project paper (Bachelor of Electrical  Engineering (Electronics)) -- Universiti Malaysia Pahang - 2009</note>
  <subject authority="lcsh">
    <topic>Human face recognition (Computer science)</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Image processing</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Biometric identification</topic>
  </subject>
  <identifier type="isbn">THE0006672(Local)</identifier>
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    <recordContentSource authority="marcorg">UMP</recordContentSource>
    <recordCreationDate encoding="marc">090714</recordCreationDate>
    <recordChangeDate encoding="iso8601">20251114204405.0</recordChangeDate>
    <recordIdentifier source="KUKTEM">vtls000040252</recordIdentifier>
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