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Image Processing for Rapidly Eye Detection based on Robust Haar Sliding Window

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 7 No. 2 (2017)

DOI
10.11591/ijece.v7i2.pp823-830
ISSN
2088-8708, 2088-8708
Published
2017-04-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

Object Detection using Haar Cascade Clasifier widely applied in several devices and applications as a medium of interaction between human and computer such as a tool control that utilizes the detection of eye movements. Obviously speed and precision in the detection process such as eyes, has an effect if implemented on a device. If the eye could not detect accurately, controlling device systems could reach bad detection as well. The proposed method can be used as an approach to detect the eye region of eye based on haar classifier method by means of modifying the direction of sliding window. In which, it was initially placed in the middle position of image on facial area by assuming the location of eyes area in the central region of the image. While the window region of conventional haar cascade scan the whole of image start from the left top corner. From the experiment by using our proposed method, it can speed up the the computation time and improve accuracy significantly reach to 92,4%.

Collaboration network of the authors

38 authors · 80 co-authorship links · 7 across different organisations

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

  • University of Brawijaya
  • Institut Teknologi Sepuluh Nopember
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Fitra Abdurrachman BachtiarUniversity of Brawijaya3
Indriati IndriatiUniversity of Brawijaya2
Hurriyatul FitriyahUniversity of Brawijaya2
Rizal MaulanaUniversity of Brawijaya2
Randy Cahya WihandikaUniversity of Brawijaya2
Muhammad Ali FauziUniversity of Brawijaya2
Dahnial SyauqyUniversity of Brawijaya2
Firnanda Al Islama Achyunda PutraUniversity of Brawijaya1
Wayan Firdaus MahmudyUniversity of Brawijaya1
Agus Zainal ArifinInstitut Teknologi Sepuluh Nopember1
Evy Kamilah RatnasariInstitut Teknologi Sepuluh Nopember1
Siti MutrofinInstitut Teknologi Sepuluh Nopember1
Fadhil Yusuf RahadikaUniversity of Brawijaya1
Novanto YudistiraUniversity of Brawijaya1
Chastine FatichahInstitut Teknologi Sepuluh Nopember1
Ratih Kartika DewiUniversity of Brawijaya1
Ihwanudien Hasan RobbaniUniversity of Brawijaya1
Enny TrisnawatiUniversity of Brawijaya1
Rakhmadina NoviyantiUniversity of Brawijaya1
Afrizal RivaldiUniversity of Brawijaya1
Waskitha WijayaUniversity of Brawijaya1
Herman TolleUniversity of Brawijaya1
Putra Pandu AdikaraUniversity of Brawijaya1
Sigit AdinugrohoUniversity of Brawijaya1
Ovy RochmawantiUniversity of Brawijaya1
Rizky Maulana IqbalUniversity of Brawijaya1
Edy SantosoUniversity of Brawijaya1
Raditya RinandyaswaraUniversity of Brawijaya1
Muhammad Tanzil FurqonUniversity of Brawijaya1
Rifki Akbar SiregarUniversity of Brawijaya1
Alfisyar Jefry PranataUniversity of Brawijaya1
Edy SantosoUniversity of Brawijaya1
Natasya Eldha OktavianaUniversity of Brawijaya1
Aisyah AwalinaUniversity of Brawijaya1
Muhammad WafiUniversity of Brawijaya1

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.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Image Processing for Rapidly Eye Detection based on Robust Haar Sliding Window</dc:title><dc:creator>Utaminingrum, Fitri</dc:creator><dc:creator>Praetya, Renaldi Primaswara</dc:creator><dc:creator>Sari, Yuita Arum</dc:creator><dc:description>&lt;jats:p&gt;Object Detection using Haar Cascade Clasifier widely applied in several devices and applications as a medium of interaction between human and computer such as a tool control that utilizes the detection of eye movements. Obviously speed and precision in the detection process such as eyes, has an effect if implemented on a device. If the eye could not detect accurately, controlling device systems could reach bad detection as well. The proposed method can be used as an approach to detect the eye region of eye based on haar classifier method by means of modifying the direction of sliding window. In which, it was initially placed in the middle position of image on facial area by assuming the location of eyes area in the central region of the image. While the window region of conventional haar cascade scan the whole of image start from the left top corner. From the experiment by using our proposed method, it can speed up the the computation time and improve accuracy significantly reach to 92,4%.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2017-04-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v7i2.pp823-830</dc:identifier><dc:identifier>10.11591/ijece.v7i2.pp823-830</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 7 No 2 (2017); 823</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/6430/6304</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>