Application of Continuous Time Quantum Walks to Image Segmentation

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Abstract

This paper provides the algorithm that applies concept of continuous time quantum walks to image segmentation problem. The work, inspired by results from its classical counterpart [9], presents and compares two versions of the solution regarding calculation of pixel-segment association: The version using limiting distribution of the walk and the version using last step distribution. The obtained results vary in terms of accuracy and possibilities to be ported to a real quantum device. The described results were obtained by simulation on classical computer, but the algorithms were designed in a way that will allow to use a real quantum computer, when ready.

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Krok, M., Rycerz, K., & Bubak, M. (2019). Application of Continuous Time Quantum Walks to Image Segmentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11537 LNCS, pp. 17–30). Springer Verlag. https://doi.org/10.1007/978-3-030-22741-8_2

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