Abstract
Humans can easily recognize specific patterns and their repetition in an image but it is very difficult for machines to do. However, the machines can create a plethora of repeated patterns and tiled images. This research paper proposes some methods of recognizing an unknown repeated motif in tiled images in computer generated raster graphics. Three approaches, autocorrelation of an image, comparing with template strip and cyclic bitwise XOR-ing of the image are compared in this paper. Finally, the third algorithm is proposed as it detects locally repeating unknown motifs in a tiled image and outperforms the former two methods in robustness and provides a reliable result. Unlike other traditional approaches, the proposed method does not require any feature extraction and clustering of features or patches and it is unsupervised.
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Acknowledgement
Authors of this paper would like to appreciate Galaincha software for making the arduous work of creating the dataset of tiled images easier and faster. Furthermore, authors are thankful for whole Galaincha Team for the continuous support during this research.
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Neupane, P., Tuladhar, A., Sharma, S., Tamang, R. (2021). Extracting Unknown Repeated Pattern in Tiled Images. In: Abraham, A., Shandilya, S., Garcia-Hernandez, L., Varela, M. (eds) Hybrid Intelligent Systems. HIS 2019. Advances in Intelligent Systems and Computing, vol 1179. Springer, Cham. https://doi.org/10.1007/978-3-030-49336-3_10
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DOI: https://doi.org/10.1007/978-3-030-49336-3_10
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