Automatic attendance capturing using histogram of oriented gradients on facial images

Abejide Ade-Ibijola, Kehinde Aruleba

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)


Humans mostly use faces to identify/recognise individuals and the recent improvement in the capability of computing now allow recognition and detection automatically. However, there still exist quite a number of problems in the automatic recognition of facial images. Histogram of Oriented Gradients (HOG) has been recently adopted and seen as a standard for efficient face recognition and object detection generally. In this paper, we investigate and discuss a simple but effective approach to capturing student's attendance register in a lecture hall by making use of HOG features for detecting and recognising students face at different moods, orientations, and illuminations. Our experiment detection and recognition output show a good performance on our facial image database obtained from the University of Johannesburg, this performance is due to HOG descriptors attributes which are robust to changes in rotation and illuminations. Our system will help to save instructional staff/lecturer time by eliminating manual calling of students name and also help monitor students.

Original languageEnglish
Title of host publication2018 IST-Africa Week Conference, IST-Africa 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781905824601
Publication statusPublished - 20 Jul 2018
Event2018 IST-Africa Week Conference, IST-Africa 2018 - Gaborone, Botswana
Duration: 9 May 201811 May 2018

Publication series

Name2018 IST-Africa Week Conference, IST-Africa 2018


Conference2018 IST-Africa Week Conference, IST-Africa 2018


  • Face recognition
  • Feature extraction
  • Histogram of oriented gradients

ASJC Scopus subject areas

  • Education
  • Computer Science Applications
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications


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