Abstract
The adequate potential of digital images and the ease in their storage and distribution is such that they are more and more exploited to supply information in this digital epoch. As a consequence, they indicate a public source of evidence in our everyday life. Beside their benefits, the accessibility of them could bring a major detriment as they can be modified easily by a media processing application.
Detection of tampering with digital images is still an open work in the image processing domain. Over the past years there has been a swift expansion in the designing and developing of image forgery detection algorithms plus related software applications. All these algorithms are divided into two groups: active and passive. In the active approaches, we create and embed invaluable data as a cipher key into the original image to protect it against the forgery,while in the passive methods we only investigate some features of the image such as statistical anomalies, correlations and compressions to detect forgery.
This chapter presents an in-depth exploration of issues related to active digital image forgery detection algorithms which are derived from cellular automata. The aim of this chapter is to give a brief but comprehensive overview of the usage of cellular automata to develop active image forgery detection techniques. We conclude with experimental results in this topic and discuss future works in image forgery detection using cellular automata.
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Tafti, A.P., Hassannia, H. (2014). Active Image Forgery Detection Using Cellular Automata. In: Rosin, P., Adamatzky, A., Sun, X. (eds) Cellular Automata in Image Processing and Geometry. Emergence, Complexity and Computation, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-319-06431-4_7
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DOI: https://doi.org/10.1007/978-3-319-06431-4_7
Publisher Name: Springer, Cham
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