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Anomaly Detection in Surveillance Video of Natural Environment

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Silas Santiago L. Pereira, José E.B. Maia

Silas Santiago L Pereira and Jose E B Maia. Anomaly Detection in Surveillance Video of Natural Environment. International Journal of Computer Applications 183(1):1-7, May 2021. BibTeX

	author = {Silas Santiago L. Pereira and Jose E.B. Maia},
	title = {Anomaly Detection in Surveillance Video of Natural Environment},
	journal = {International Journal of Computer Applications},
	issue_date = {May 2021},
	volume = {183},
	number = {1},
	month = {May},
	year = {2021},
	issn = {0975-8887},
	pages = {1-7},
	numpages = {7},
	url = {},
	doi = {10.5120/ijca2021921288},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


This work demonstrates the effectiveness of the median filter combined with morphological operators in the detection of anomalies in video surveillance of scenes of natural environment. Natural environment is characterized by backgrounds that are not static but whose dynamics are limited and do not include the appearance or disappearance of background objects in the scene. Examples include background images with seawater or river surfaces, or landscapes with trees, in which the wind produces waves and other movements of limited amplitude. The performance on four publicly available benchmark videos is compared to that of other published state-of-the-art works. The results obtained are promising.


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Anomaly detection, background extraction, median filter, morphology operator, intelligent video surveillance