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Related Experiment Videos

Unified camera tamper detection based on edge and object information.

Gil-beom Lee¹, Myeong-jin Lee², Jongtae Lim³

¹School of Electronics, Telecommunication & Computer Engineering, Korea Aerospace University, 76 Hanggongdaehak-ro Deogyang-gu, Goyang-si, Gyeonggi-do 412-791, Korea. lgbch2@gmail.com.

Sensors (Basel, Switzerland)

|May 7, 2015

Summary

This study introduces a new camera tamper detection algorithm to identify covered, moved, or defocused attacks. The method uses an edge disappearance rate and adaptive threshold for reliable real-world camera security.

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Area of Science:

Computer Vision
Security Systems
Image Processing

Background:

Camera systems are vulnerable to various tamper attacks.
Effective detection of camera tampering is crucial for security.
Existing methods may lack robustness in diverse environmental conditions.

Purpose of the Study:

To propose a novel algorithm for detecting camera tamper attacks.
To address the detection of covered, moved, and defocused tamper types.
To develop a method robust to varying environmental conditions.

Main Methods:

Definition of an edge disappearance rate to quantify changes from background frames.
Exclusion of foreground edges to focus on background alterations.
Utilizing an adaptive threshold based on environmental conditions for detection.
Real-time video sequence analysis for performance evaluation.

Main Results:

The algorithm successfully detects covered, moved, and defocused tamper attacks.
Acceptable detection rates were achieved across all tested tamper types.
Low false alarm rates were observed in real-world environments.
Performance validated on both short and 24-hour video sequences.

Conclusions:

The proposed camera tamper detection algorithm offers effective and robust security.
The edge disappearance rate metric provides a reliable indicator of tampering.
The adaptive threshold enhances detection accuracy under dynamic environmental conditions.
This algorithm presents a viable solution for enhancing surveillance system security.