Anomaly and tampering detection of cameras by providing details

Hosseini, Sayyed Mohammad; Taherinia, Amir Hossein

doi:10.1109/iccke.2016.7802134

Cited by 5 publications

(1 citation statement)

References 11 publications

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“…However, in case of physical anomalies, such as the ones derived from changes in the environmental conditions, the integrity assessment strategy would have to be different. For that case, there have been several studies on camera tampering detection [5], [6], with methods to identify obstruction or an unintended change in the camera position. These methods, usually based on edge detection [7], are employed for surveillance cameras and require a static or known background plane, being unsuitable for situations where the scenery is dynamic or unknown.…”

Section: Introductionmentioning

confidence: 99%

Partial Camera Obstruction Detection Using Single Value Image Metrics and Data Augmentation

Oliveira

Niemi

García-Ortiz

et al. 2022

2022 6th International Conference on System Reliability and Safety (ICSRS)

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To improve the resilience and ensure the dependability of a critical system, the measurements and the derived intelligence provided by the sensors monitoring the system need to be reliable. This is increasingly challenging. As the computer vision methods evolve, the usage of cameras as a part of monitoring solutions has increased, and, consequently, the need for reliable diagnosis strategies for those image-based sensors. This work investigates the suitability of various single-value image metrics, derived from first and second-order statistics, for detecting partial camera obstruction. The presented methodology includes using data augmentation techniques to expand a small dataset of labeled images, and a score-based selection of the best metrics for the target application. The results show that even simple first-order statistics, such as the image histogram skewness, can provide good detection results. The strategy presented could be extended and adapted for the detection of other types of physical anomalies, being particularly useful for integrity assessment in applications with limited computational resources.

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Section: Introductionmentioning

confidence: 99%