Embedding and extracting method for wavelet domain chaotic semi-frageile digit water print

Abstract

The present invention relates to the embedding and extracting method of wavelet chaotic semi-fragile digital water print. Original image is 2D two-stage wavelet analyzed to obtain {LL2, HL2, LH2, HH2, HL1, LH1, HH1}, where, the pixel grey of LL2 sublayer is mapped to form chaotic initial value and chaotically iterated for several times to form water print image. Then, based on the quantized medium frequency coefficients { HL2, LH2, HH2}, and by means of the extreme sensitivity of chaos to the initial value and the excellent temporal frequency characteristic of wavelet, the distortion to water print image is precisely located. Via flexible regulation of quantized parameters, the robustness against baleful attack is obtained. The method of the present invention has stable performance, fast realizing speed, strong robustness to baleful distortion and excellent distortion locating and proving capacity.

Description

Technical field: [0001] The invention relates to a wavelet domain chaotic semi-fragile digital watermark embedding and extraction method, which is a semi-fragile digital watermark embedding and extraction method especially suitable for digital product authentication, content tampering location and integrity certification. Background technique: [0002] In recent years, digital watermarking technology has increasingly shown its superior performance in copyright protection and content authentication of digital products. The research on robust digital watermarking for copyright protection has been in-depth. The robust watermarking with excellent performance should be designed to resist most attacks, and the copyright information of digital products can still be preserved after suffering from these attacks. However, considering the content integrity certification of digital products and the credibility of transmitted multimedia data, this watermarking technology cannot fully mee...

AI Technical Summary

Problems solved by technology

[0006] Question 1. The above-mentioned similar algorithms cannot tolerate JPEG compression or additive Gaussian white noise, and they are also considered malicious attacks without distinction.

[0007] Question 2. The above algorithm shares the same LSB plane at different levels, resulting in mutual inclusion of embedded content. Therefore, a segmentation algorithm is needed to solve the collision problem during embedding.

[0008] Question 3, similar to these traditional tampering location methods are generally based on the sensitivity of the Hash function to tampering

[0011] Problem 1, can only resist a small degree of JPEG compression

[0012] Problem two, the peak signal-to-noise ratio of the watermarked image is too low

[0013] Question 3, the vector quantization codebook must be designed offline, and the codebook must be transmitted for watermark extraction

However, the existing technology has not been able to solve these problems well.

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