Abstract
Detecting unknown repeated patterns that appear multiple times in a digital image is a great challenge. We have addressed this problem in a recent work and we have shown that, using a compression based approach, it is possible to find exact repetitions. In this work, we continue this study, introducing a procedure for detecting unknown repeated patterns that occur in a close vicinity. We use finite-context modelling to pinpoint the possible locations of the repetitions, by exploring the connection between lossless image compression and image complexity. Since repetitions are associated to low complexity regions, the repeating patterns are revealed and easily detected. The experimental results show that the proposed approach provides increased ability to eliminate false positives.
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Pratas, D., Pinho, A.J. (2012). On the Detection of Unknown Locally Repeating Patterns in Images. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2012. Lecture Notes in Computer Science, vol 7324. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31295-3_19
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DOI: https://doi.org/10.1007/978-3-642-31295-3_19
Publisher Name: Springer, Berlin, Heidelberg
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