Intelligent moving objects detection via adaptive frame differencing method

Chun Ming Tsai*, Zong Mu Yeh

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)


The detection of moving objects is a critical first step in video surveillance, but conventional moving objects detection methods are not efficient or effective for certain types of moving objects: slow and fast. This paper presents an intelligent method to detect slow- and fast-moving objects simultaneously. It includes adaptive frame differencing, automatic thresholding, and moving objects localization. The adaptive frame differencing uses different inter-frames for frame differencing, the number depending on variations in the differencing image. The thresholding method uses a modified triangular algorithm to determine the threshold value and reduces most small noises. The moving objects localization uses six cascaded rules and bounding-boxes-based morphological operations to merge broken objects and remove noise objects. The fps value (maximum 72) depends on the speed of the objects. The number of inter-frames is inversely proportional to the speed. The results demonstrate that our method is more efficient than traditional frame differencing and background subtraction methods.

Original languageEnglish
Title of host publicationIntelligent Information and Database Systems - 5th Asian Conference, ACIIDS 2013, Proceedings
Number of pages11
EditionPART 1
Publication statusPublished - 2013
Event5th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2013 - Kuala Lumpur, Malaysia
Duration: 2013 Mar 182013 Mar 20

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume7802 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference5th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2013
CityKuala Lumpur


  • Adaptive frame differencing
  • Bounding-boxes-based morphological operations
  • Moving objects Detection
  • Video surveillance
  • background subtraction

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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