• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.527-530
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• 2008

The watermarking method was suggested to protect the right of the copyright and the right of property, data loss is yes or not, copy prevention and pursuit about the brainchild(music, image, video and so on) in the early 1990. In this paper, we suggest the watermarking algorithm against the geometrical transformation of the medical images applied the Watershed algorithm. The robust watermarking methodology is being suggested using the several algorithm against the attacks such as compression, filtering, noise and geometrical transformation of the medical image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11A
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• pp.870-881
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• 2009

The rapid development of healthcare information management for 3D medical digital library, 3D PACS and 3D medical diagnosis has addressed security issues with medical IT technology. This paper presents multiple 3D medical image data for protection, authentication, indexing and diagnosis information hiding applied to healthcare information management. The proposed scheme based on POCS watermarking embeds the robust watermark for doctor's digital signature and information retrieval indexing key to the distribution of vertex curvedness and embeds the fragile watermark for diagnosis information and authentication reference message to the distance difference of vertex. The multiple embedding process designs three convex sets for robustness, fragileness and invisibility and projects 3D medical image data onto three convex sets alternatively and iteratively. Experimental results confirmed that the proposed scheme has the robustness and fragileness to various 3D geometric and mesh modifiers at once.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.255-258
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• 2003

Recently, Digital Watermarking is used to authenticate data and to determine whether the data are distorted or not in medical images which is digitalized. The Fourier Mellin method using the Fourier Transform and the Log-Polar coordinate transform gets an invariant feature for RST distortion in images. But there are several problems in the real materialization. Interpolation of the image value should be considered according to the pixel position and so a watermark loss, original image distortion, numerical approximation is happened. Therefore there should be solved to realization of the Fourier Mellin method. Using the Look up table, there reduce the data loss caused by the conversion between Rectangular and Polar coordinate. After diagnose, medical images are transformed the Polar coordinate and taken the Discrete Fourier transform in the center of ROI region. Maintaining the symmetry in Fourier magnitude coefficient, the gaussian distributed random vectors and binary images are embedded in medical images.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2621-2623
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• 2003

본 논문에서는 의료 영상에 대한 새로운 연성 워터마크 알고리즘을 제안한다. 본 알고리즘을 사용함으로써 의료 영상의 보안 및 위조 문제를 해결 할 수 있다. 제안한 알고리즘은 이산 웨이블릿 변환을 사용하는 대신에 계산량이 적은 정수 웨이블릿 변환을 이용하여 블록 평균을 이용해서 이진 비트맵을 추출하여 이를 워터마크 정보로 사용한다. 워터마크를 추출할 때는 원 영상의 정보를 나타내는 이진 비트맵과 비교함으로써 위조여부를 판단할 수 있다. 실험을 통하여 제안한 알고리즘은 의료 영상의 위조된 부분을 정확하게 추출하는 것을 확인하였다.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2537-2539
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• 2003

본 논문에서는 의료 영상에 대한 저작권보호를 위한 새로운 워터마킹 알고리즘을 제안한다. 본 알고리즘에서는 이산 웨이블릿 변환 대신에 계산량이 적은 정수 웨이블릿 변환을 이용하였다. 본 논문에서는 정수 웨이블릿 공간에서 유사-잡음 수열을 워터마크로 삽입 하였다. 워터마크를 추출할 때 확산스펙트럼 기법을 이용하고 유사도는 공분산 수열에서 결정한다. 실험을 통하여 제안한 알고리즘이 노이즈, 압축 등 공격에 강인함을 보임을 확인하였다.

• The KIPS Transactions:PartB
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• v.17B no.4
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• pp.275-286
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• 2010

Reversible watermarking which can preserve the original quality of the digital contents and protect the copyright has been studied actively. Especially, in medical, military, and art fields, the need for reversible watermarking is increasing. This paper proposes a high-capacity reversible watermarking through predicted error expansion and error estimation compensation. Watermark is embedded by expanding the difference histogram between the original value and the predicted value. Differently from previous methods calculating the difference between adjacent pixels, the presented method calculates the difference between the original value and the predicted value, and that increases the number of the histogram value, where the watermark is embedded. As a result, the high capacity is achieved. The inserted watermark is extracted by restoring the histogram between the original value and the predicted value. To prove the performance, the presented algorithm is compared with other previous methods on various test images. The result supports that the presented algorithm has a perfect reversibility, a high image quality, and a high capacity.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.415-417
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• 2004

저작권보호를 목적으로 사용하는 워터마킹 기술은 원본 이미지에 특정 워터마크 정보를 삽입하는데 이러한 경우, 원본이미지는 다시 복구할 수 없다. 의료영상 데이터베이스나 군사용 이미지 시스템과 같은 특정된 응용에서는 이미지 열화가 시스템 전체에 미치는 영향이 크기 때문에 이러한 워터마크 알고리즘을 사용할 수 없다. 본 연구에서는 Hadamard Matrix(HM)을 이용하여 디지털 이미지에 워터마크를 삽입하며, 가역적인 연산에 기초하여 원 이미지의 복구가 가능하도록 워터마크 알고리즘을 개발한다. 본 연구에서는 Hadamard Coefficients의 규칙적인 연관성을 이용하여 2D HM을 알고리즘 개발에 적용한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.759-766
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• 2017

In this paper, we preserve the transparency of digital contents by compressing and storing the medical image for a certain period so as to be safe and robust against various attacks of medical images. The proposed algorithm generates an encrypted image authentication code that extracts the feature value of the original image and combines it with the user's information. in order to extract hidden data, the authentication code is first decrypts the encrypted medical image and extracts the hidden data using the spatial characteristics of image. The proposed algorithm guarantees integrity when comparing extracted authentication code and newly generated authentication code for image authentication after directly inserting it into content itself through watermarking. We have proved various security of attack of image data and proved that the certification rate is improved to 98.4%.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.1088-1094
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• 2010

Image authentication algorithms have to discriminate forged contents in the various critical fields of military, medical services, digital documents. They must ensure perceptual invisibility and fragility against malicious attacks. It is desirable that watermarking algorithms support sufficient insertion capacity and blind feature. And, high reliable algorithms that can eliminate false-positive and false-negative errors are needed in the watermark extraction process. In this paper, we control coefficients of high frequency band in a DCT domain and compensate brightness histogram for high reliability. As a result, we found that the proposed algorithm guarantee various requirements such as perceptual invisibility with high PSNR values, fragility, high reliability and blind feature. In addition, experiment results show that the proposed algorithm can be used steganographic applications by sufficient capacity of watermark.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.203-208
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• 2019

Digital watermarking was developed to protect copyright by discouraging the illegal copying of digital content. On the other hand, recently, watermarking has also been used to verify the integrity of digital content, such as medical images, and detect illegal manipulation or distortion locations. Watermarking should be tenacious so as to protect copyright from illegal copying and should remain firm to the content through a range of attacks, such as distortion or filtering. At the same time, however, it should be removed easily even in a slight transformation of the material to verify the integrity. Therefore, this paper proposes a watermarking technique that easily checks and verifies the deformation or manipulation of digital images. In the proposed method, the entire image was examined in $16{\times}16$ blocks to check for deformation of the image. When deformation was detected, further inspection proceeded in $4{\times}4$ blocks and the location where deformation occurred was identified.