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Binary Wavelet Transform-Based Financial Text Image Authentication Algorithm

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Abstract

This paper presents a novel financial text image security authentication algorithm based on binary wavelet transform. Initially, the algorithm preprocesses the original financial text image using binary wavelet transform. Subsequently, it categorizes the pixels in each low-frequency subband image block based on their flippability. The “nonflippable” pixels are then hashed to generate watermark information, which replaces the “flappable” pixels in the corresponding mapping block to embed the watermark into the low-frequency subband. By studying the characteristics of high-frequency coefficients, the algorithm identifies the flippable coefficients in the frequency domain and uses block mapping to embed high-frequency subband encryption watermark information. The authenticity of the image block is verified by comparing the consistency between the reconstructed watermark and the extracted watermark. Furthermore, the “low-frequency-high-frequency subband joint judgment criterion” is employed to enhance tampering detection performance. Our experimental results indicate that the structural similarity (SSIM) of financial text images embedded with watermarks using this algorithm is above 0.99, satisfying the human visual system’s image quality requirements. Under different tampering attack rates, the missed-detection probability and false-detection probability of this algorithm are lower than those of existing methods. It is also compatible with financial text image compression algorithms, making it suitable for tampering detection of important financial text images.

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REFERENCES

  1. Kota, S. and Pal, R., Detecting tampered cheque images in cheque truncation system using difference expansion based watermarking, 2014 IEEE Int. Advance Computing Conf. (IACC), Gurgaon, India, 2014, IEEE, 2014, pp. 1041–1047. https://doi.org/10.1109/iadcc.2014.6779469

  2. Gonge, S.S. and Ghatol, A., A robust and secure DWT-SVD digital image watermarking using encrypted watermark for copyright protection of cheque image, Security in Computing and Communications. SSCC 2015, Abawajy, J., Mukherjea, S., Thampi, S., and Ruiz-Martínez, A., Eds., Communications in Computer and Information Science, vol. 536, Springer, 2015, pp. 290–303. https://doi.org/10.1007/978-3-319-22915-7_28

  3. Mohanarathinam, A., Kamalraj, S., Prasanna Venkatesan, G.K.D., Ravi, R.V., and Manikandababu, C.S., Digital watermarking techniques for image security: A review, J. Ambient Intell. Hum.ized Comput., 2020, vol. 11, no. 8, pp. 3221–3229. https://doi.org/10.1007/s12652-019-01500-1

    Article  Google Scholar 

  4. Kumar, C., Singh, A.K., and Kumar, P., A recent survey on image watermarking techniques and its application in e-governance, Multimedia Tools Appl., 2018, vol. 77, no. 3, pp. 3597–3622. https://doi.org/10.1007/s11042-017-5222-8

    Article  Google Scholar 

  5. Molina-Garcia, J., Garcia-Salgado, B.P., Ponomaryov, V., Reyes-Reyes, R., Sadovnychiy, S., and Cruz-Ramos, C., An effective fragile watermarking scheme for color image tampering detection and self-recovery, Signal Process.: Image Commun., 2020, vol. 81, p. 115725. https://doi.org/10.1016/j.image.2019.115725

    Article  Google Scholar 

  6. Yeung, Yu., Lu, W., Xue, Yi., Huang, J., and Shi, Yu.-Q., Secure binary image steganography with distortion measurement based on prediction, IEEE Trans. Circuits Syst. Video Technol., 2019, vol. 30, no. 5, pp. 1423–1434. https://doi.org/10.1109/tcsvt.2019.2903432

    Article  Google Scholar 

  7. Lu, W., He, L., Yeung, Yu., Xue, Yi., Liu, H., and Feng, B., Secure binary image steganography based on fused distortion measurement, IEEE Trans. Circuits Syst. Video Technol., 2018, vol. 29, no. 6, pp. 1608–1618. https://doi.org/10.1109/tcsvt.2018.2852702

    Article  Google Scholar 

  8. Yeung, Yu., Lu, W., Xue, Yi., Chen, J., and Li, R., Secure binary image steganography based on LTP distortion minimization, Multimedia Tools Appl., 2019, vol. 78, no. 17, pp. 25079–25100. https://doi.org/10.1007/s11042-019-7731-0

    Article  Google Scholar 

  9. Lu, W., Li, R., Zeng, L., Chen, J., Huang, J., and Shi, Yu.-Q., Binary image steganalysis based on histogram of structuring elements, IEEE Trans. Circuits Syst. Video Technol., 2019, vol. 30, no. 9, pp. 3081–3094. https://doi.org/10.1109/tcsvt.2019.2936028

    Article  Google Scholar 

  10. Alotaibi, R.A. and Elrefaei, L.A., Text-image watermarking based on integer wavelet transform (IWT) and discrete cosine transform (DCT), Appl. Comput. Inf., 2019, vol. 15, no. 2, pp. 191–202. https://doi.org/10.1016/j.aci.2018.06.003

    Article  Google Scholar 

  11. Laouamer, L. and Tayan, O., A semi-blind robust DCT watermarking approach for sensitive text images, Arabian J. Sci. Eng., 2015, vol. 40, no. 4, pp. 1097–1109. https://doi.org/10.1007/s13369-015-1596-y

    Article  Google Scholar 

  12. Kwon, O.-J., Kim, W.-G., and Kim, Yo., Binary image watermarking with tampering localization in binary wavelet transform domain, Int. J. Multimedia Ubiquitous Eng., 2012, vol. 7, no. 2, pp. 341–346. https://www.earticle.net/Article/A202156.

  13. Li, J. and Wu, F., Robust watermarking for text images based on Arnold scrambling and DWT-DFT, Proc. 2013 Int. Conf. on Mechatronic Sciences, Electric Engineering and Computer (MEC), Shengyang, China, 2013, IEEE, 2013, pp. 1182–1186.

  14. Cao, H. and Kot, A.C., EAG: Edge adaptive grid data hiding for binary image authentication, Proc. 2012 Asia Pacific Signal and Information Processing Assoc. Annu. Summit and Conf., Hollywood, Calif., 2012, IEEE, 2012, pp. 1–6.

  15. Chen, F., Qin, Ya., and He, H., Multi-block dependency based watermarking scheme for binary-text image authentication, Signal and Information Processing Assoc. Annu. Summit and Conf. (APSIPA), 2014 Asia-Pacific, Siem Reap, Cambodia, 2014, IEEE, 2014, pp. 1–5. https://doi.org/10.1109/apsipa.2014.7041611

  16. Qi, W., Guo, W., Zhang, T., Liu, Yu., Guo, Z., and Fang, X., Robust authentication for paper-based text documents based on text watermarking technology, Math. Biosci. Eng., 2019, vol. 16, no. 4, pp. 2233–2249. https://doi.org/10.3934/mbe.2019110

    Article  MathSciNet  Google Scholar 

  17. Tan, L., Hu, K., Zhou, X., Chen, R., and Jiang, W., Print-scan invariant text image watermarking for hardcopy document authentication, Multimedia Tools Appl., 2019, vol. 78, no. 10, pp. 13189–13211. https://doi.org/10.1007/s11042-018-5771-5

    Article  Google Scholar 

  18. Dubey, P., Kanumuri, T., and Vyas, R., Palmprint recognition using binary wavelet transform and LBP representation, 2017 Int. Conf. on Recent Innovations in Signal processing and Embedded Systems (RISE), Bhopal, India, 2017, IEEE, 2017, pp. 201–205. https://doi.org/10.1109/rise.2017.8378154

  19. Li, Q. and Xu, X., Fast target detection of surface ship based on improved YOLOV3-tiny, Comput. Eng., 2021, vol. 47, no. 10, pp. 283–289, 297.

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Funding

This work was supported by National Natural Science Foundation of China under contract no. 61803178.

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Authors and Affiliations

  1. School of Computer Science and Technology, Liaocheng University, 252000, Liaocheng, China

    Wenjin Wang

  2. School of Business, Liaocheng University, 252000, Liaocheng, China

    Miaomiao Lu

  3. First System Sector, CETC Ocean Information Co. Ltd., 572400, Sanya, China

    Xuanling Dai

  4. School of Electrical Engineering, University of Jinan, 250022, Jinan, China

    Ping Jiang

Authors
  1. Wenjin Wang
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  2. Miaomiao Lu
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  3. Xuanling Dai
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  4. Ping Jiang
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Correspondence to Wenjin Wang.

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Wenjin Wang, Lu, M., Dai, X. et al. Binary Wavelet Transform-Based Financial Text Image Authentication Algorithm. Aut. Control Comp. Sci. 58, 326–335 (2024). https://doi.org/10.3103/S0146411624700202

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