Foreground detection using motion histogram threshold algorithm in high-resolution large datasets

Fakhri Alam Khan, Muhammad Nawaz, Muhammad Imran*, Arif Ur Rahman, Fawad Qayum

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Background subtraction, being the most cited algorithm for foreground detection, encounters the major problem of proper threshold value at run time. For effective value of the threshold at run time in background subtraction algorithm, the primary component of the foreground detection process, motion is used, in the proposed algorithm. For the said purpose, the smooth histogram peaks and valley of the motion were analyzed, which reflects the high and slow motion areas of the moving object(s) in the given frame and generates the threshold value at run time by exploiting the values of peaks and valley. This proposed algorithm was tested using four recommended video sequences, including indoor and outdoor shoots, and were compared with five high ranked algorithms. Based on the values of standard performance measures, the proposed algorithm achieved an average of more than 12.30% higher accuracy results.

Original languageEnglish
Pages (from-to)667-678
Number of pages12
JournalMultimedia Systems
Issue number4
StatePublished - Aug 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2020, Springer-Verlag GmbH Germany, part of Springer Nature.


  • Background subtract
  • Foreground detection
  • Intelligent video surveillance

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Media Technology
  • Hardware and Architecture
  • Computer Networks and Communications


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