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Frontal Face Detection using Haar Wavelet Coefficients and Local Histogram Correlation

Journal of ICT Research and Applications (JICTRA) · Vol. 5 No. 3 (2013) · pp. 157–172

DOI
10.5614/itbj.ict.2011.5.3.1
ISSN
2338-5499, 2337-5787
Published
2013-09-13
Publisher
DRI - ITB
Language
eng

Abstract

Face detection is the main building block on which all automatic systems dealing with human faces is built. For example, a face recognition system must rely on face detection to process an input image and determine which areas contain human faces. These areas then become the input for the face recognition system for further processing. This paper presents a face detection system designed to detect frontal faces. The system uses Haar wavelet coefficients and local histogram correlation as differentiating features. Our proposed system is trained using 100 training images. Our experiments show that the proposed system performed well during testing, achieving a detection rate of 91.5%.

Collaboration network of the authors

11 authors · 23 co-authorship links · 9 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Satya Wacana Christian University
  • Universitas Raharja
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Regina LionnieSatya Wacana Christian University2
Untung RahardjaUniversitas Raharja1
Ninda LutfianiUniversitas Raharja1
Irwan SembiringSatya Wacana Christian University1
Adi SetiawanSatya Wacana Christian University1
Sulistio SulistioUniversitas Raharja1
Septian AbednegoSatya Wacana Christian University1
Gunawan DewantoroSatya Wacana Christian University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journals.itb.ac.id/index.php/jictra/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="en-US">Frontal Face Detection using Haar Wavelet Coefficients and Local Histogram Correlation</dc:title>
	<dc:creator>Setyawan, Iwan</dc:creator>
	<dc:creator>Timotius, Ivanna K.</dc:creator>
	<dc:creator>Febrianto, Andreas A.</dc:creator>
	<dc:description xml:lang="en-US">Face detection is the main building block on which all automatic systems dealing with human faces is built. For example, a face recognition system must rely on face detection to process an input image and determine which areas contain human faces. These areas then become the input for the face recognition system for further processing. This paper presents a face detection system designed to detect frontal faces. The system uses Haar wavelet coefficients and local histogram correlation as differentiating features. Our proposed system is trained using 100 training images. Our experiments show that the proposed system performed well during testing, achieving a detection rate of 91.5%.</dc:description>
	<dc:publisher xml:lang="en-US">DRI - ITB</dc:publisher>
	<dc:date>2013-09-13</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journals.itb.ac.id/index.php/jictra/article/view/213</dc:identifier>
	<dc:identifier>10.5614/itbj.ict.2011.5.3.1</dc:identifier>
	<dc:source xml:lang="en-US">Journal of ICT Research and Applications; Vol. 5 No. 3 (2011); 157-172</dc:source>
	<dc:source>2338-5499</dc:source>
	<dc:source>2337-5787</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journals.itb.ac.id/index.php/jictra/article/view/213/207</dc:relation>
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