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Analysis and improvement of the quantum image matching

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Abstract

We investigate the quantum image matching algorithm proposed by Jiang et al. (Quantum Inf Process 15(9):3543–3572, 2016). Although the complexity of this algorithm is much better than the classical exhaustive algorithm, there may be an error in it: After matching the area between two images, only the pixel at the upper left corner of the matched area played part in following steps. That is to say, the paper only matched one pixel, instead of an area. If more than one pixels in the big image are the same as the one at the upper left corner of the small image, the algorithm will randomly measure one of them, which causes the error. In this paper, an improved version is presented which takes full advantage of the whole matched area to locate a small image in a big image. The theoretical analysis indicates that the network complexity is higher than the previous algorithm, but it is still far lower than the classical algorithm. Hence, this algorithm is still efficient.

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References

  1. Jiang, N., Dang, Y., Wang, J.: Quantum image matching. Quantum Inf. Process. 15(9), 3543–3572 (2016)

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Author information

Authors and Affiliations

  1. Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China

    Yijie Dang, Nan Jiang & Hao Hu

  2. Beijing Key Laboratory of Trusted Computing, Beijing, 100124, China

    Yijie Dang, Nan Jiang & Hao Hu

  3. National Engineering Laboratory for Critical Technologies of Information Security Classified Protection, Beijing, 100124, China

    Yijie Dang, Nan Jiang & Hao Hu

  4. School of Information Science and Technology, Linyi University, Linyi, 276000, China

    Wenyin Zhang

Authors
  1. Yijie Dang
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  2. Nan Jiang
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  3. Hao Hu
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  4. Wenyin Zhang
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Corresponding author

Correspondence to Nan Jiang.

Additional information

This work is supported by the National Natural Science Foundation of China under Grant No. 61502016, the International Research Cooperation Seed Fund of BJUT, the Joint Open Fund of Information Engineering Team in Intelligent Logistics under Grant No. LDXX2017KF152, and the Natural Science Foundation of Shandong Province under Grant Nos. ZR2016FM40 and ZR2016YL011.

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Dang, Y., Jiang, N., Hu, H. et al. Analysis and improvement of the quantum image matching. Quantum Inf Process 16, 269 (2017). https://doi.org/10.1007/s11128-017-1723-7

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  • DOI: https://doi.org/10.1007/s11128-017-1723-7

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