Study on the detection and recovery algorithm of important financial information tampering
by Wenjin Wang; Xinghua Liu; Yuxin Zhang; Jia Liu; Ping Jiang
International Journal of Information and Communication Technology (IJICT), Vol. 21, No. 3, 2022

Abstract: A self-recovery watermarking algorithm for important financial information content authentication is proposed in this paper. The algorithm firstly pre-processes the source image with wavelet transform and divides sub-band image for low frequency into sub-blocks. Secondly, in order to ensure the accuracy of the localisation of the tampered area, a dual authentication watermarking mechanism called 'SVD-position recording' is adopted for each image block. Thirdly, the source images are down-scaled and segmented based on K-mediods clustering to generate a binary code stream of vital information, taking into account the watermark capacity and recovery quality. Finally, the binary code stream is knight's parade scrambled and RS error-corrected coded to be embedded in the high-frequency wavelet coefficients which reduce the possibility of recovery watermark tampering. Experimental results show that the peak signal-to-noise ratio (PSNR) of the financial document images with embedded watermark by the algorithm in this paper is above 43 dB, which has excellent visual quality. At the same time, it achieves accurate localisation and precise recovery for tampering attacks such as add, copy, and delete, which is suitable for tampering detection and recovery of important financial information.

Online publication date: Wed, 14-Sep-2022

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