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
New opportunities in computer-aided diagnosis: change detection and characterization.
Proceedings ArticleDOI
Efficient Change Detection for Very Large Motion Blurred Images
TL;DR: This paper devise an algorithm for judicious sub-image selection so that the camera motion can be deciphered correctly, irrespective of the presence or absence of occluder, and follows a reblur-difference framework to detect changes.
Proceedings ArticleDOI
Change detection and classification in brain MR images using change vector analysis
TL;DR: This paper presents an unsupervised 3D change detection method based on Change Vector Analysis that is able to detect and discriminate both small changes and ventricle expansions in datasets from Mild Cognitive Impairment patients.
Proceedings ArticleDOI
A block-based clustering technique for real time object detection on a static background
TL;DR: This paper presents a block-based clustering technique applied on blocks of the absolute difference that presents the additional benefit of increased robustness against large-scale image alterations.
Journal ArticleDOI
Deep learning-based scene-awareness approach for intelligent change detection in videos
TL;DR: An approach that integrates several detection techniques with scene understanding capability, thereby overcoming the challenges of detecting various scene types and improving overall detection performance and can serve as an intelligent change detection approach for visual analytics in video surveillance systems.
References
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Journal ArticleDOI
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