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Reversible Data Hiding Utilizing Two-Dimensional Prediction Errors

This paper presents a novel method for reversible data hiding based on two-dimensional prediction errors. The authors review related work before proposing their own scheme, which effectively exploits prediction errors for embedding data within images. The process involves scanning cover images, predicting pixel values, generating a two-dimensional histogram, and partitioning it to select embedding channels. Experimental results demonstrate the scheme's effectiveness and versatility for designing robust, multi-dimensional data hiding architectures. This research has implications for secure image communication.

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Reversible Data Hiding Utilizing Two-Dimensional Prediction Errors

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  1. Reversible Data Hiding Based on Two-Dimensional Prediction Errors Source : IET Image Processing, Vol. 7, No. 9, pp. 805-816, 2013 Authors :Shyh-Yih Wang, Chun-Yi Li and Wen-Chung Kuo Speaker : Min-Hao Wu Date :2014/03/17

  2. Outline • Related work – Yang et al.’s scheme • Proposed scheme • Experimental results • Conclusions

  3. Yang’s Proposed scheme (1/6)

  4. Yang’s Proposed scheme Proposed scheme (2/6) Embedding Process of odd columns P1 P2 Z2 Z1 H

  5. Yang’s Proposed scheme Proposed scheme(3/6) Embedding Process of odd columns • Rule: • Embed bit 0, keep unchanged • Embed bit 1, P2 -1 or P1 +1, respectively B1=01110011001 D’

  6. Yang’s Proposed scheme Proposed scheme(6/6)

  7. Embedding process • Step 1: • scan the cover image and apply the two prediction methods to predict the pixel values in the image. • For each scanned pixel, let (e1, e2) denote the prediction errors.

  8. Embedding process • Step 2: • generate the 2D histogram, H(e1, e2). • Step 3: • split the e1 − e2 plane into channels and partition the histogram H(e1, e2) correspondingly. • Step 4: • select ‘embedding channels (ECs)’, which are the channels for embedding messages. • Step 5: • for each EC, use a 1D embedding technique to embed the message.

  9. Proposed scheme(chessboard, C-2D) (2,2) (2,2) Prediction error e1 (2,2) Cover image X For example : x1’(2, 2) = (150+150+150+153)/4 = 150 x2’ (2, 2) =(150+150)/2 = 150 Prediction error e2

  10. Proposed scheme(chessboard, C-2D) pr pl c = 0 e1 e2 Cover image X Result after histogram H(e1, e2) e’1 e’2 Result after shifting Result after shifting channel 0

  11. Proposed scheme(chessboard, C-2D) pr = (0, 0) pl = (-2, -2) Secret bit : 1001110(2) e”2 e’2 e’1 e”1 Result after shifting Stego image Y

  12. Proposed scheme(chessboard, C-2D) pr = (0, 0) pl = (-2, -2) Stego image Y e”1 Secret bit : 1001110(2) Cover image X

  13. Proposed scheme(framework) c ∈ [−cb, cb] Channel 0 (e1, e2) : denote the two prediction errors for a pixel Part of a practical histogram H(e1, e2) generated from Lena

  14. 15

  15. Experimental results

  16. Conclusions • This scheme can be used to design 2D reversible data-hiding schemes is presented. • This framework can be applied to any architecture, and it can easily be extended into a multi-dimensional framework.

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