DWT-Based Data Hiding Technique for Videos Ownership Protection DOI: http://dx.doi.org/10.5772/intechopen.84963

correlation values using our detection algorithm, while Figure 14 shows the PSNRs of the reconstructed frames. Figure 15 shows the PSNRs for the proposed watermarking method and the method of [20] when different numbers of frames of Football video were used. The method of [20] gives a maximum PSNR of 30 dB for the Football video, while our method gives an average of 42 dB; moreover, the performance in terms of NCs for the Football video stream using our method and the method in [20] was evaluated. The NC of method in [20] has an average value of 0.73, while our method gave a smooth performance with an average value of 0.99; this was shown as well in Figure 13.

For further investigation and evaluation of the robustness of our technique, the test videos will be subjected to some familiar attacks. These include additive noise, cropping, sharpening, rotating, frame averaging process, and HEVC compression. The attacks have the following characteristics:


Figure 14. PSNRs of the test videos when the proposed watermarking process is used.

Figure 15.

PSNRs of the proposed method (the blue line) and method of [20] (the green line) when different numbers of frames of the video sequence Football are used.

Figure 10.

Wavelet Transform and Complexity

Figure 11.

Figure 12.

Figure 13.

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(a) Original watermark and (b) recovered watermark.

Normalized correlations of the proposed watermarking process.

Correlation values of the extracted watermarks using our detection process.

The first frame of (a) original BasketballDrill frame and (b) watermarked BasketballDrill frame.

The results for each attack for the different standard videos are shown in Figure 16.

To ensure the robustness of the algorithm, it was tested with the application of HEVC process. HEVC process with a quantization parameter (QP) value of 20 was applied to 100 frames of the test videos. Different compression ratios will result depending on each input video when this quantization factor is used. First, the watermarking process was applied to the test video frames and without applying the enhancement process. The PSNRs are shown in Figure 17, and the NCs at the watermarked frames are shown in Figure 18. A significant observation here is that lower values will result in the frames between 80 and 90 for the Football video, and this can be attributed to the blurring effects in these frames as a result of the fast panning of the camera. This, in turn, would result in lower energy in the DWT coefficients, and it is possible to overcome this phenomenon by our enhanced

DWT-Based Data Hiding Technique for Videos Ownership Protection

The correlations, moreover, were evaluated when the proposed detection process was applied. The watermarks were embedded randomly in multiple frames; then they were extracted and processed according to the method in Section 3. A number of frames being used for embedding process are 20%, 50%, and ultimately 100% of the 100 test frames of the proposed standard videos. Figure 19 shows the performance under these circumstances. It can be shown that the detection process was enhanced dramatically when comparing with Figure 18. The system can perform well even with only 20% of the frames being watermarked. To evaluate our algorithm under different compression ratios, the standard test videos were watermarked and compressed using HEVC with different QPs: 15, 20, and 25. The value of 20 is a typical value for compression. Figure 20 shows the performance of our system under these compression values. As QP becomes larger than 25, the video qualities go through noticeable degradation in terms of resolutions; in fact, the system performs well for QP values of 20 or less, and as QP values reach 25, the detection process starts to lose its efficiency for some videos. This is due to the aggressive quantization process of the discrete cosine transform (DCT) coefficients

Our selective denoising filter which was introduced in Section 4 was tested for the watermarked videos. The standard videos were watermarked according to the proposed embedding process; then they were subjected to salt-and-pepper noise

Correlations vs. number of frames being watermarked when our detection method is used.

Watermarking process performance under different quantization parameters.

detection process as we will see later.

DOI: http://dx.doi.org/10.5772/intechopen.84963

in the HEVC process.

Figure 19.

Figure 20.

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Figure 16.

Performance of the watermarking process under common aggressive attacks.

Figure 17. PSNRs of the proposed watermarking method when HEVC process is applied.

Figure 18. Normalized correlations of the proposed watermarking method when HEVC process is applied.
