Journal ArticleDOI
Image change detection algorithms: a systematic survey
TLDR
In this paper, the authors present a systematic survey of the common processing steps and core decision rules in modern change detection algorithms, including significance and hypothesis testing, predictive models, the shading model, and background modeling.Abstract:
Detecting regions of change in multiple images of the same scene taken at different times is of widespread interest due to a large number of applications in diverse disciplines, including remote sensing, surveillance, medical diagnosis and treatment, civil infrastructure, and underwater sensing. This paper presents a systematic survey of the common processing steps and core decision rules in modern change detection algorithms, including significance and hypothesis testing, predictive models, the shading model, and background modeling. We also discuss important preprocessing methods, approaches to enforcing the consistency of the change mask, and principles for evaluating and comparing the performance of change detection algorithms. It is hoped that our classification of algorithms into a relatively small number of categories will provide useful guidance to the algorithm designer.read more
Citations
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Journal ArticleDOI
Change Detection Based on the Coefficient of Variation in SAR Time-Series of Urban Areas
TL;DR: This paper discusses change detection in SAR time-series, and several criteria that are based on ratios of coefficients of variations are proposed to detect long events, such as construction test sites, or point-event,such as vehicles.
Journal ArticleDOI
Tracking of Defects in Reinforced Concrete Bridges Using Digital Images
TL;DR: In this article, a set of dimensionless metrics pertinent to fractal analysis of digital images is proposed for the periodic detection of defects in concrete bridges based on the set of fractal dimensions.
Journal ArticleDOI
Statistical Change Detection by the Pool Adjacent Violators Algorithm
Alessandro Lanza,L. Di Stefano +1 more
TL;DR: A statistical change detection approach aimed at being robust with respect to the main disturbance factors acting in real-world applications such as illumination changes, camera gain and exposure variations, noise.
Proceedings ArticleDOI
Background subtraction in people detection framework for RGB-D cameras
Anh-Tuan Nghiem,Francois Bremond +1 more
TL;DR: In this paper, a background subtraction algorithm specific for depth videos from RGB-D cameras is proposed, embedded in a people detection framework, which outperforms GMM, a popular background subtracted algorithm, in detecting people and removing noise.
Journal ArticleDOI
On the nature and types of anomalies: a review of deviations in data.
TL;DR: In this article, the authors present a theoretically principled and domain-independent typology of data anomalies and presents a full overview of anomaly types and subtypes, including cardinality of relationship, anomaly level, data structure, and data distribution.
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