• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1980-1987
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• 2000

In this paper, an efficient watermarking technique in wavelet transform domain is proposed. Watermarking is embedding a digital signal called as 'watermark' into images to claim the ownership. In the proposed method, the image is 1-level wavelet transformed, and then the watermark with a binary stamp is embedded into the baseband. The watermark is embedded by inverting the polarities of he selected coefficient paris. In the inverting process, we can increase image quality by finding means and differences of the selected neighboring coefficient paris, and then adding values, which are inversely proportional to the differences, to th means. The experimental results show that the proposed method has good quality and is robust to various attacks such as the JPEG lossy comparison, noise addition, clipping, blurring, etc.

• Journal of the Korea Computer Industry Society
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• v.3 no.7
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• pp.871-880
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• 2002

In this paper, I proposed the adaptive watermarking based on the discrete wavelet transform for the very robust watermarking against intentional distortion which attacks on image. A watermark is an binary image such as document(sign), and such watermark image is embedded in the LH and HL band of wavelet transformed domain for copyright protection of image data. To evaluate robustness of the proposed method, we applied some basic algorithm of image processing such as brightening, darkening, sharpening, blurring, cropping, histogram equalizing and lossy compression(JPEG, gif). As a result of experiment, the proposed method has the good image quality and the high perceptibility of watermark. It was demonstrated by experiments that the proposed algorithm can provide an excellent protection under various attacks.

• International Journal of Contents
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• v.11 no.3
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• pp.39-46
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• 2015

When host images are watermarked with CRT (Chinese Remainder Theorem), the watermark images are still robust in spite of the damage of the host images by maintaining the remainders in an unchanged state within some range of the changes that are incurred by the attacks. This advantage can also be attained by "zero-watermarking," which does not change the host images in any way. This paper proposes an improved zero-watermarking scheme for color images on the DCT (Discrete Cosine Transform) domain that is based on the CRT. In the scheme, RGB images are converted into YCbCr images, and one channel is used for the DCT transformation. A key is then computed from the DC and three low-frequency AC values of each DCT block using the CRT. The key finally becomes the watermark key after it is combined four times with a scrambled watermark image. When watermark images are extracted, each bit is determined by majority voting. This scheme shows that watermark images are robust against a number of common attacks such as sharpening, blurring, JPEG lossy compression, and cropping.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.466-469
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• 2000

In this paper, a watermarking technique for digital images is proposed. In our method, an image is 1-1eve1 wavelet transformed, and then the watermark of a binary stamp is embedded into the baseband. The watermark is embedded by inverting the polarities of the selected coefficient pairs. In the inverting process, we can increase perceptual image quality by finding means and differences of the selected neighboring coefficient pairs, and then adding values, which are inversely proportional to the differences, to the means. The experimental results show that the proposed method has good quality and is robust to JPEG lossy compression and various image processing operations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.3B
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• pp.557-564
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• 2000

This paper presents a watermarking algorithm for embedding visually recognizable pattern (Mark, Logo, Symbol, stamping or signature) into the image. first, the color image(RGB model)is transformed in YCbCr model and then the Y component is transformed into 3-level wavelet transform. Next, the values are assembled with pattern watermark. PN(pseudo noise) code at spread spectrum communication method and mutilevel watermark weights. This values are inserted into discrete wavelet domain. In our scheme, new calculating method is designed to calculate wavelet transform with integer value in considering the quantization error. and we used the color conversion with fixed-point arithmetic to be easy to make the hardware hereafter. Also, we made the new solution using mutilevel threshold to robust to common signal distortions and malicious attack, and to enhance quality of image in considering the human visual system. the experimental results showed that the proposed watermarking algorithm was superior to other similar water marking algorithm. We showed what it was robust to common signal processing and geometric transform such as brightness. contrast, filtering. scaling. JPEG lossy compression and geometric deformation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.112-115
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• 2022

The process of deep learning usually needs to deal with massive data which has greatly limited the development of deep learning technologies today. Convolutional Neural Network (CNN) structure is often used to solve image classification problems. However, a large number of images may be required in order to train an image in CNN, which is a heavy burden for existing computer systems to handle. If the image data can be compressed under the premise that the computer hardware system remains unchanged, it is possible to train more datasets in deep learning. However, image compression usually adopts the form of lossy compression, which will lose part of the image information. If the lost information is key information, it may affect learning performance. In this paper, we will analyze the effect of image compression on deep learning performance on CNN-based cat and dog classification. Through the experiment results, we conclude that the compression of images does not have a significant impact on the accuracy of deep learning.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.9-20
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• 2000

In this paper we compare two frequency domain digital watermarking methods for digital Images, namely DCT(Discrete Cosine Transform) based and DFT(Discrete Fourier Transform) based methods. Unlike DCT coefficients, which always have real values, DFT coefficients normally have complex values Therefore, the DFT coefficients have amplitude and phase components Among them, the phase components are known to carry more Important information for the Images. So, we insert the watermark to the phase of the DFT coefficients only This DFT watermarking method is compared with the conventional DCT based watermarking method for the object-based watermarking problem. Experimental results show that the DFT-phase based method IS more robust to general Image processing attacks including resize, lossy compression(JPEG), blurring and median filtering. On the other hand, the DCT based method is more robust to the malicious attack which inserts different watermarks.

• Journal of KIISE:Software and Applications
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• v.30 no.10
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• pp.938-943
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• 2003

In this paper, we Propose a method using the Tikhonov-Miller process to improve the robustness of watermarking under various attacks. A visually recognizable pattern watermark is embedded in the LH2, HL2 and HH2 subband of wavelet transformed domain using threshold and besides watermark is embeded by utilizing HVS(Human Visual System) feature. The pattern watermark was interlaced after random Permutation for a security and an extraction rate. To demonstrate the improvement of robustness and similarity of the proposed method, we applied some basic algorithm of image processing such as scaling, filtering, cropping, histogram equalizing and lossy compression(JPEG, gif). As a result of experiment, the proposed method was able to embed robust watermark invisibility and extract with an excellent normalized correlation of watermark under various attacks.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.3
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• pp.21-27
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• 2002

The digital watermarking methods have been proposed as a solution for solving the illegal copying and proof of ownership problems in the context of multimedia data. But it is still difficult to have been overcame the problem of the protection of property to multimedia data, such as digital images, digital video, and digital audio. This paper describes a watermarking algorithm that embeds non-linearly audio logo watermark data which is converted from audio signal of the ownership in the components of pixel intensities in an original image and that insists of ownership by hearing the audio signal transformed from the extracted audio logo through the speaker. Experimental results show that our algorithm using audio logo proposed in this paper is robust against attacks such as particularly lossy JPEG image compression. 

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3885-3895
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• 2000

The emergence of digital imaging and digital networks has made duplication of original artwork easier. In order to protect these creations, new methods for signing and copyrighting visual data are needed. In the last few years, a large number of schemes have heen proposed for hiding copyright marks and other information in digital image, video, audio and other multimedia objects. In this paper, we propose a technique for embedding the watermark of visually recognizable patterns into the frequency domain of images. The embedded watermark can be retrieved from the decoded sequence witbout knowledge of the original. Because the source image is not required to extract the watermark, one cannot make the fake original that is invertible to watermarking scheme from the waternlarked image. In order to recover the embedded signature data without knowledge of the original, a prediction of the original value of the pixel containing the information is needed. The prediction is based on a averaging of amplitude values in a neighborhood around the pixel itself. Additionally the projxJsed technique could survive several kinds of image processings including JPEG lossy compression.