Analisis Deteksi Tepi Citra Dengan Quantum Hadamard Edge Detection (QHED)

Authors

  • Lipantri Mashur Gultom Politeknik Negeri Bengkalis
  • Desi Amirullah Politeknik Negeri Bengkalis

DOI:

https://doi.org/10.33633/tc.v21i4.6708

Keywords:

Quantum, Hadamard, Edge Detection

Abstract

Fokus penelitian ini pada eksperimen Quantum Hadamard Edge Detection (QHED) untuk pendeteksian tepi suatu gambar dimana jumlah qubit yang digunakan ternyata sangat mempengaruhi waktu pemrosesan CPU. Penelitian ini mengunakan benchmark dataset gambar yaitu contour detection and image segmentation dari Berkeley Computer Vision Group. Jumlah qubit yang digunakan pada penelitian ini yaitu 2, 4, 6, 8, 10 dan 12 qubit, sedangkan jumlah qubit lebih dari 12 tidak dapat diuji karena keterbatasan memori RAM dari perangkat yang ada dalam penelitian ini. Hasil akhir dari penelitian membuktikan bahwa QHED dapat mendeteksi tepi suatu gambar dimana waktu pemrosesan yang paling cepat pada penggunaan 6 qubit sedangkan hasil proses pendeteksian tepi yang terbaik terletak pada penggunaan 2 qubit.

References

F. Yan and S. E. Venegas-Andraca, “Quantum image processing,” Quantum Image Process., pp. 1–171, 2020, doi: 10.1007/978-981-32-9331-1.

F. Yan, A. M. Iliyasu, and P. Q. Le, “Quantum image processing: a review of advances in its security technologies,” Int. J. Quantum Inf., vol. 15, no. 03, p. 1730001, 2017.

S. Pramanik et al., “Quantum image processing,” Phys. Rev. X, vol. 7, no. 3, pp. 1–171, 2020, doi: 10.1103/PhysRevX.7.031041.

W. S. Gan, “Quantum Image Processing,” in Quantum Acoustical Imaging, Singapore: Springer Singapore, 2022, pp. 83–86.

A. Anand, M. Lyu, P. S. Baweja, and V. Patil, “Quantum image processing,” 2022, [Online]. Available: http://arxiv.org/abs/2203.01831.

A. Geng, A. Moghiseh, C. Redenbach, and K. Schladitz, “A hybrid quantum image edge detector for the NISQ era,” Quantum Mach. Intell., vol. 4, no. 2, pp. 1–19, 2022, doi: 10.1007/s42484-022-00071-3.

Y. Ruan, X. Xue, and Y. Shen, “Quantum Image Processing: Opportunities and Challenges,” Math. Probl. Eng., vol. 2021, 2021, doi: 10.1155/2021/6671613.

J. Su, X. Guo, C. Liu, and L. Li, “A new trend of quantum image representations,” IEEE Access, vol. 8, pp. 214520–214537, 2020.

S. Yuan, S. E. Venegas-Andraca, Y. Wang, Y. Luo, and X. Mao, “Quantum Image Edge Detection Algorithm,” Int. J. Theor. Phys., vol. 58, no. 9, pp. 2823–2833, 2019, doi: 10.1007/s10773-019-04166-9.

G. Cavalieri and D. Maio, “A Quantum Edge Detection Algorithm,” 2020, [Online]. Available: http://arxiv.org/abs/2012.11036.

X. W. Yao et al., “Quantum image processing and its application to edge detection: Theory and experiment,” Phys. Rev. X, vol. 7, no. 3, 2017, doi: 10.1103/PhysRevX.7.031041.

P. Arbeláez, M. Maire, C. Fowlkes, and J. Malik, “Contour detection and hierarchical image segmentation,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 5, pp. 898–916, 2011, doi: 10.1109/TPAMI.2010.161.

S. Pramanik et al., “A Quantum-Classical Hybrid Method for Image Classification and Segmentation,” 2021, [Online]. Available: http://arxiv.org/abs/2109.14431.

J. Canny, “A Computational Approach to Edge Detection,” IEEE Trans. Pattern Anal. Mach. Intell., vol. PAMI-8, no. 6, pp. 679–698, 1986, doi: 10.1109/TPAMI.1986.4767851.

F. G. Irwin and others, “An isotropic 3x3 image gradient operator,” Present. Stanford AI Proj., vol. 2014, no. 02, 1968.

Downloads

Published

2022-11-30

Issue

Vol. 21 No. 4 (2022): November 2022

Section

Articles

License

Copyright (c) 2022 Lipantri Mashur Gultom

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

 

License Terms

All articles published in Techno.COM Journal are licensed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). This means:

1. Attribution

Readers and users are free to:

  • Share – Copy and redistribute the material in any medium or format.

  • Adapt – Remix, transform, and build upon the material.

As long as proper credit is given to the original work by citing the author(s) and the journal.

2. Non-Commercial Use

  • The material cannot be used for commercial purposes.

  • Commercial use includes selling the content, using it in commercial advertising, or integrating it into products/services for profit.

3. Rights of Authors

  • Authors retain copyright and grant Techno.COM Journal the right to publish the article.

  • Authors can distribute their work (e.g., in institutional repositories or personal websites) with proper acknowledgment of the journal.

4. No Additional Restrictions

  • The journal cannot apply legal terms or technological measures that restrict others from using the material in ways allowed by the license.

5. Disclaimer

  • The journal is not responsible for how the published content is used by third parties.

  • The opinions expressed in the articles are solely those of the authors.

For more details, visit the Creative Commons License Page:
? https://creativecommons.org/licenses/by-nc/4.0/

 

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.