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A New Method for Tamper Detection and Recovery. Speaker : Kuo-Lung Hung ( 洪國龍 ) Date : 2001.01.18. Problem Definition. The definition of tampered detection and recovery.
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A New Method for Tamper Detection and Recovery Speaker : Kuo-Lung Hung (洪國龍) Date : 2001.01.18
Problem Definition The definition of tampered detection and recovery When somebody modified an specific image, the technique that candetect the tamper, and, moreover, can recover the modification.
Requirement • Effectiveness: • Differentiation: • Security: • Recoverability: Provide a very high probability of tamper detection. Can distinguish between an innocent adjustment and replacing or adding features. Provide the security mechanism; only a selected group of people sharing a secret key should perform the detection. Can recover back to the correct image from the modification.
Previous Work • Using the indices of the codewords of size 16(for detection) and the low-bit rate compressed image, namely the indices of the codewords of size 256 (for recovery) as the watermark. • To hide the watermark to the middle-frequency DCT coefficient. • The detection codewords of a block are hiding in the itself block, and its recovery codewords are hiding in the randomly selected block. Problem • The security is not enough. • The number of hiding bits is too many (= 32 bits/per block). Therefore, the method can not endure some image adjustment operations.
The proposed method Three techniques employed by our method: • Watermark Generating • Watermark Embedding • Tamper Detecting and Recovering
Watermark Generating 8 45 48 50 53 • Divide the image into 88 blocks. 47 55 50 52 • Divide a block into 44 sub-blocks. 8 51 46 • Calculate the mean values of the sub-blocks of a block to form a 4-dimensional vector. 60 65 78 80 90 85 4 4
Watermark Generating (cont.) 0 40,50,50,48 1 • Use these vectors to generate local codebook of size 512. 0 50,50,50,55 50,50,50,55 2 1 3 • Perform the pseudo-gray coding upon the codebook. 2 . . . 3 511 . . . After pseudo-gray coding 511 40,50,50,48 • The codebook is used to encode the vector of each block, and some indices are obtained. • Use the RS coding to encode the codewords of the codebook. (for error correction) 16 bit/per block Watermark = the indices + checksums of the indices +the RS-encoded codewords
Image Adjustment Before Embedding the value after VQ decoding : 48 The distortion exists between the mean value of each sub-block and the value after VQ decoding. 50 53 40 43 40 43 53 50 48 45 38 35 53 50 40 43 40 43 50 53 50 53 48 45 the mean value : 45 53 50 48 45 43 40 53 50 • Calculate the mean value of each sub-block. • Subtract the mean value and add the value after VQ decoding to each pixel. Motivation Image adjustment
Watermark Embedding DCT coefficients 1 2 6 7 15 162829 3 5 8 14 172730 43 4 9 13 182631 42 44 10 12 1925 32 41 45 54 • Randomly hide the scrambled watermark to the middle-frequency DCT coefficients of each block. 11 2024 33 40 46 53 55 2123 34 39 47 52 56 61 22 35 38 48 51 57 60 62 36 37 49 50 58 59 63 64 • Totally scramble the watermark.
Example: =2 mj 4+2 if wj=1, H(mj,wj) = H(mj,1) = (mj / 8) 8 + 4 4 Mj+2 4 if wj=0, 4 H(mj,0) = ((mj +4)/ 8) 8 E(mj) = 0 if ((mj+) mod 4 ) < 2 , 1 otherwise. Watermark Embedding (cont.) Bit hiding eg. H(0,1)->4, H(6,1)-> 4, H(10,1)->12 where 1 is the adjusting magnitude. eg. H(0,0)->0, H(6,0)-> 8, H(10,0)->8 Bit extracting
Detection and Recovery tampered if Abs(Mi - Mj) > threshold, not tampered otherwise. the block is: • Use the bit extracting function to extract the hided watermark. • Since the extracted watermark might have some errors, the error correction technique needs performed upon the watermark. • According to the extracted watermark, the hided mean value Mi of each sub-block could be obtained. • Calculate the mean value Mj of the sub-block that might have been tampered with. Therefore,
Remarks • The proposed tamper proofing technique can securely and effectively detect and recover the image that tampered with. • Compare to previous work, the security is enhanced, moreover, the proposed technique can distinguish between an innocent adjustment and intentional modification. • The image adjustment may loss some image quality. • If the range of the modification is large, the detection has some false drops. • To alleviate the problem of (3) and (4) is the future work.