CAJ | 학술논문

以离散余弦变换(DCT)和矩阵奇异值分解(SVD)为基础，结合Quick Response(QR)码的高容量、高纠错特性，提出了一种适合QR码的强鲁棒性数字水印算法。首先，提取QR码图像中的寻像和分隔符图形，并进行高斯加噪模糊化处理，把得到的QR码灰度图像作为载体图像，同时对水印图像进行Arnold置乱处理。然后，对载体图像进行8×8的分块DCT变换，取每块的直流系数得到矩阵A(64×64)，对A进行SVD分解，并在A的奇异值处嵌入水印信息。实验结果表明：该算法在不影响QR码正确识别的基础上，不仅具有较好的不可见性，而且对如叠加高斯噪声、椒盐噪声、泊松噪声和中值滤波等攻击均具有很好的鲁棒性。
이리산여현변환(DCT)화구진기이치분해(SVD)위기출，결합Quick Response(QR)마적고용량、고규착특성，제출료일충괄합QR마적강로봉성수자수인산법。수선，제취QR마도상중적심상화분격부도형，병진행고사가조모호화처리，파득도적QR마회도도상작위재체도상，동시대수인도상진행Arnold치란처리。연후，대재체도상진행8×8적분괴DCT변환，취매괴적직류계수득도구진A(64×64)，대A진행SVD분해，병재A적기이치처감입수인신식。실험결과표명：해산법재불영향QR마정학식별적기출상，불부구유교호적불가견성，이차대여첩가고사조성、초염조성、박송조성화중치려파등공격균구유흔호적로봉성。
The proposes a new robust digital watermarking method for Quick Response (QR) code images, which was based on Discrete Cosine Transformation (DCT) and singular value decomposition (SVD). The new method fully takes advantage of the high- capacity property and a good error- correction ability of QR code. Firstly, position detection was performed to extract pattern positions and separators in a given QR image and then fuzzify the image with Gaussian noise to form a carrier image. At the meanwhile, the watermarking image was scrambled with Arnold transform. Next, transformation with DCT were done on the basis of 8’8 blocks and whose DC coefficients were put together to form a matrix A with a dimension of 64’64. Finally, watermarking image can be embedded in singular values of matrix A after applying SVD to it. Experimental results show that the algorithm was robust in resisting attacks such as Gaussian noise, salt & pepper noise, speckle noise and median filter without affecting the correct identification of QR code.