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Image change detection algorithms: a systematic survey
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.
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Cites
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Graph based anomaly detection and description: a survey
Akoglu, L., Tong, H., & Koutra, D. (2015) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-014-0365-y · Cited by 1,504
the DIARETDB1 diabetic retinopathy database and evaluation protocol
Kauppi, T., Kalesnykiene, V., Kamarainen, J.-K., Lensu, L., Sorri, I., Raninen, A., Voutilainen, R., Uusitalo, H., Kalviainen, H., & Pietila, J. (2007) · Procedings of the British Machine Vision Conference 2007 · doi:10.5244/c.21.15 · Cited by 854
Spatiotemporal Data Mining: A Computational Perspective
Shekhar, S., Jiang, Z., Ali, R., Eftelioglu, E., Tang, X., Gunturi, V., & Zhou, X. (2015) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi4042306 · Cited by 206
Machine vision for natural gas methane emissions detection using an infrared camera
Wang, J., Tchapmi, L. P., Ravikumar, A. P., McGuire, M., Bell, C. S., Zimmerle, D., Savarese, S., & Brandt, A. R. (2020) · Applied Energy · doi:10.1016/j.apenergy.2019.113998 · Cited by 205
Real-Time Change Point Detection with Application to Smart Home Time Series Data
Aminikhanghahi, S., Wang, T., & Cook, D. J. (2019) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2018.2850347 · Cited by 123
Metadata
- Authors
- Radke, R. J., Andra, S., Al-Kofahi, O., & Roysam, B.
- Venue
- IEEE Transactions on Image Processing
- Published
- 2005-03
- Volume
- 14
- Issue
- 3
- Pages
- 294-307
- ISSN
- 1057-7149 (ISSN-L)
- OpenAlex
- W2170140722
- Cited by
- 1,869
- References
- 4
- FWCI
- 215.47
- Type
- journal article
- Language
- en
- Open access
- closed
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