Fuzzy Logic Based Perceptual Image Hashing Algorithm in Malaysian Banknotes Detection System for the Visually Impaired

Authors

  • Wai Kit Wong Multimedia University
  • Chi Jie Tan Faculty of Engineering and Technology, Multimedia University (MMU), Jalan Ayer Keroh Lama, Melaka, 75450, Malaysia
  • Thu Soe Min Faculty of Engineering and Technology, Multimedia University (MMU), Jalan Ayer Keroh Lama, Melaka, 75450, Malaysia
  • Eng Kiong Wong Faculty of Engineering and Technology, Multimedia University (MMU), Jalan Ayer Keroh Lama, Melaka, 75450, Malaysia

DOI:

https://doi.org/10.30564/aia.v3i1.3249

Abstract

Visually impaired persons have difficulty in business that dealing with banknote. This paper proposed a Malaysian banknotes detection system using image processing technology and fuzzy logic algorithm for the visually impaired. The Malaysian banknote reader will first capture the inserted banknote image, sending it to the cloud server for image processing via Wi-Fi medium. The cloud server is established to receive the banknote image sending from the banknote reader, processing them using perceptual hashing based image searching and fuzzy logic algorithm, then return the detected banknote’s value results back to the banknote reader. The banknote reader will display the results in terms of voice message played on the mini speaker attached on it, to allow visually impaired persons knowing the banknote’s value. This hardware mechanism reduces the size and costs for the banknote reader carried by the visually impaired persons. Experimental results showed that this Malaysian banknotes detection system reached an accuracy beyond 95% by running test on 600 different worn, torn and new Malaysian banknotes. After the banknote image being taken by the banknote reader’s camera, the system able to detect the banknote value in about 480 mili-seconds to 560 mili-seconds for a single sided banknote recognition. The banknotes detection speed was also comparable with human observers reading banknotes, with the response of 1.0908 second per banknote slight difference reading time. The IoT and image processing concepts were successfully blended and it provides an alternative to aid the visually impaired person their daily business transaction activities in a better way.

Keywords:

Fuzzy logic; Image processing; Banknote reader; Malaysian banknote; Visually impaired

References

[1] S. C. Reddy, T. Thevi, "Blindness and low vision in Malaysia," International Journal of Ophthalmic Research, vol. 3, no. 2, pp. 234-238, 2017.

[2] S. P. Khanal, K. P. Acharya, P. Uprety, S. K. Shah, "Statistical Modeling on Blindness and Visual Impairment Data," Journal of Institute of Science and Technology, vol. 19, no. 1, pp. 1-6, 2014.

[3] T. M. e. al, "The Eurosystem´s efforts in the search for a longer lasting banknote," Billetaria, no. 9, 2011.

[4] N. A. Semary, S. M. Fadl, M. S. Essa, A. F. Gad, "Currency Recognition System for Visually Impaired: Egyptian Banknote as a Study Case," in IEEE 2015 International Conference on Information and Communication technology and Accessibility, ICTA , Morocco, 2015.

[5] H. d. Heij, "Durable Banknotes: An Overview," in Presentation of the BPC/Paper Committee to the BPC/General Meeting, Prague, 2002.

[6] Quintero, "Evaluation of Long Lasting Papers for Venezuelan Banknotes," in XVII Pacific Rim Banknote Printers’ Conference, 2005.

[7] V. Aleven, E. A. McLaughlin, R. A. Glenn and K. R. Koedinger, “Instruction based on adaptive learning technologies”. In: Handbook of Research on Learning and Instruction, Routledge, 2016.

[8] S.Y. Lin, J.Y. Chen, J. C. Li, W. Y. Wen, S. C. Chang, "A novel fuzzy matching model for lithography hotspot detection," in IEEE/ACM Design Automation Conference (DAC), 2013.

[9] D. Raychaudhuri and N. B. Mandayam, "Frontiers of Wireless and Mobile Communications," Proceedings of the IEEE, vol. 100, no. 4, pp. 824-840, 2012.

[10] T. K. B. Das, “A Secure Image Hashing Technique for Forgery Detection. In Distributed Computing and Internet Technology”, Lecture Notes in Computer Science; Natarajan, R., Barua, G., Patra, M.R., Eds.; Springer: Cham, Switzerland, 2015; Volume 8956, p.p. 335–338

[11] H. Yang, J. Yin and M. Jiang. “Perceptual Image Hashing Using Latent Low-Rank Representation and Uniform LBP”. Applied Sciences. 2018; 8(2):317 p.p 1-12.

[12] C. S. Lu and C. Y. Hsu “Geometric distortion-resilient image hashing scheme and its applications on copy detection and authentication”. Multimedia Syst. 2005, 11, p.p. 159–173.

[13] L . A. Zadeh, Fuzzy Sets, Fuzzy Logic, Fuzzy Systems. World Scientific Press , 1996.

[14] A. P. Pujiputra, H. Kusuma and T. A. Sardjono, "Ultraviolet Rupiah Currency Image Recognition using Gabor Wavelet," 2018 International Seminar on Intelligent Technology and Its Applications (ISITIA), 2018, pp. 299-303.

[15] J.-R. Gao, B. Yu, and D. Z. Pan, “Accurate lithography hotspot detection based on pca-svm classifier," Proc. of SPIE, 2014, p.p. 90530E 1-10.

[16] V. Aleven, E. A. McLaughlin, R. A. Glenn, K.R. Koedinger. “Instruction based on adaptive learning technologies”. In: Handbook of Research on Learning and Instruction, Routledge, 2016.

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How to Cite

Wong, W. K., Tan, C. J., Min, T. S., & Wong, E. K. (2021). Fuzzy Logic Based Perceptual Image Hashing Algorithm in Malaysian Banknotes Detection System for the Visually Impaired. Artificial Intelligence Advances, 3(1), 44–56. https://doi.org/10.30564/aia.v3i1.3249

Issue

Vol. 3 , Iss. 1 (April 2021)

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