• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.99-105
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• 2015

As increasing the use of smart phones, the interest of iOS and Android operating system is growing up. In this paper, a novel steganographic method based on Android platform is proposed. Firstly, we analyze the skia based image format that is supporting 2D graphic libraries in Android operating system. Then, we propose a new data hiding method based on the Android bitmap image format. The proposed method hides the secret data on the four true color areas which include Alpha, Red, Green, Blue. In especial, we increase the embedding capacity of the secret data on the Alpha area with a less image distortion. The experimental results show that the proposed method has a higher embedding capacity and less distortion by changing the size of the secret bits on the Alpha area.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.4
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• pp.165-172
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• 2006

In this paper we present a technique for detecting cross-reference points that allows improving watermark detect-ability. In general, Harris detector is commonly used for finding salient points. Harris detector is a kind of combined corner and edge detector which is based on neighboring image data distribution, therefore it has some limitation to find accurate salient points after watermark embedding or any kinds of digital attacks. The new method proposed in this paper used not data distribution but geometrical structure of a normalized image in order to avoid pointing error caused by the distortion of image data. After normalization, we constructed pre-specified number of virtual lines from top to bottom and left to right, and several of cross points were selected by a random key. These selected points specify almost same positions with the accuracy more than that of Harris detector after digital attacks. These points were arranged by a random key, and blocks centered in these points were formed. A reference watermark is formed by a block and embedded in the next block. Because same alteration is applied to the watermark generated and embedded blocks. the detect-ability of watermark is improved even after digital attacks.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.763-764
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• 2017

The use of barcodes in mobile phones has become generalized, and barcodes are widely used in security-sensitive applications, including mobile payment and personal identification. Generally, images photographed by a mobile phone generate geometric distortion due to the shooting angle, resulting in low quality images. Embedding watermark for low quality images makes it difficult to satisfy transparency. To solve such problem, this paper focuses on the technique of embedding barcode images in the image taken by mobile phone and proposes barcode watermarking for protecting mobile-based ownership. The barcode watermark embedded in the image can be used to prove ownership since it is readable by a machine such as illegal copy.

• The Journal of the Acoustical Society of Korea
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• v.20 no.2
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• pp.66-76
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• 2001

Conventional echo watermarking techniques often exhibit inherent trade-offs between imperceptibility and robustness. In this paper, a new echo embedding technique is proposed. The proposed method enables one to embed high energy echoes while the host audio quality is not deteriorated, so that it is robust to common signal processing modifications and resistant to tampering. It is possible due to echo kernels that are designed based on psychoacoustic analyses. In addition, we propose some novel techniques to improve robustness against signal processing attacks. Subjective and objective evaluations confirmed that the proposed method could improve the robustness without perceptible distortion.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.8
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• pp.1484-1490
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• 2007

The Cross Reference Point(CRP) is a robust method for finding salient points in watermarking systems because it is based on the geometrical structure of a normalized image in order to avoid pointing error caused by digital attacks. After normalization of an image, the 100 CRPs are calculated. Next, the 100 blocks centered by CRPS are formed. These 100 blocks are arranged using a secrete key. Each boundary of 50 out of 100 blocks is surrounded by 8 blocks which are selected by the ordered number of a preceding block. This number is a seed of random number generator for selecting 8 out of 50 blocks. The search area of a center block is formed by a secrete key. The pixels of a center block are quantized to 10 levels by predefined thresholds. The watermarks are generated by the 50 quantized center blocks. These watermarks are embedded directly in the remaining 50 blocks. In other words, 50 out of 100 blocks are utilized to generate watermarks and the remaining 50 blocks are used to watermark embedding. Because the watermarks are generated in the given images, we can successfully detect watermarks after several digital attacks. The reason is that the blocks for the generation and detection of watermarks are equally affected by digital attacks except for the case of local distortion such as cropping.

• Journal of Korea Multimedia Society
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• v.6 no.3
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• pp.508-517
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• 2003

This paper presents perceptual model with a stochastic multiresolution characteristic that can be applied with watermark embedding in the biorthogonal wavelet domain. The perceptual model with adaptive watermarking algorithm embeds at the texture and edge region for more strongly embedded watermark by the SSQ. The watermark embedding is based on the computation of a NVF that has local image properties. This method uses non- stationary Gaussian and stationary Generalized Gaussian models because watermark has noise properties. The particularities of embedding in the stationary GG model use shape parameter and variance of each subband regions in multiresolution. To estimate the shape parameter, we use a moment matching method. Non-stationary Gaussian model uses the local mean and variance of each subband. The experiment results of simulation were found to be excellent invisibility and robustness. Experiments of such distortion are executed by Stirmark 3.1 benchmark test.

• The KIPS Transactions:PartB
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• v.18B no.1
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• pp.1-10
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• 2011

Reversible watermarking inserts watermark into digital media in such a way that visual transparency is preserved, which enables the restoration of the original media from the watermarked one without any loss of media quality. It has various applications, where high capacity and high visual quality are major requirements. This paper presents a new effective multi-round embedding scheme for the differential histogram-based reversible watermarking that satisfies high capacity requirements of the application. The proposed technique exploits the row-column cross scanning to fully utilize the locality of images when multi-round embedding phase to the message inserted image. Through experiments using multiple kinds of test images, we prove that the presented algorithm provides 100% reversibility, effectiveness of multi-round embedding, and higher visual quality, while maintaining the induced-distortion low.

• Journal of KIISE:Information Networking
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• v.30 no.1
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• pp.30-37
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• 2003

In this paper, a discrete wavelet transform (DWT)-based watermarking system is proposed. The main feature of proposed system is that the embedding system uses adaptive thresholds to control the trade-off between the qualify of the watermarked image and the capacity of the watermark, and the trade-off between the quality and robustness of the watermarked image. Also, the extracting system rebuilds threshold according to various attacks and decides a watermark bit from the least distorted coefficient after measuring the distortion of coefficient. Finally, a new measure to detect the uniqueness of watermark is proposed. The experimental result shows that the proposed watermarking system is robust against conventional signal processing and intentional attacks.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.127-146
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• 2022

Recently, as word embedding has shown excellent performance in various tasks of deep learning-based natural language processing, researches on the advancement and application of word, sentence, and document embedding are being actively conducted. Among them, cross-language transfer, which enables semantic exchange between different languages, is growing simultaneously with the development of embedding models. Academia's interests in vector alignment are growing with the expectation that it can be applied to various embedding-based analysis. In particular, vector alignment is expected to be applied to mapping between specialized domains and generalized domains. In other words, it is expected that it will be possible to map the vocabulary of specialized fields such as R&D, medicine, and law into the space of the pre-trained language model learned with huge volume of general-purpose documents, or provide a clue for mapping vocabulary between mutually different specialized fields. However, since linear-based vector alignment which has been mainly studied in academia basically assumes statistical linearity, it tends to simplify the vector space. This essentially assumes that different types of vector spaces are geometrically similar, which yields a limitation that it causes inevitable distortion in the alignment process. To overcome this limitation, we propose a deep learning-based vector alignment methodology that effectively learns the nonlinearity of data. The proposed methodology consists of sequential learning of a skip-connected autoencoder and a regression model to align the specialized word embedding expressed in each space to the general embedding space. Finally, through the inference of the two trained models, the specialized vocabulary can be aligned in the general space. To verify the performance of the proposed methodology, an experiment was performed on a total of 77,578 documents in the field of 'health care' among national R&D tasks performed from 2011 to 2020. As a result, it was confirmed that the proposed methodology showed superior performance in terms of cosine similarity compared to the existing linear vector alignment.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.953-960
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• 2014

In Shamir's (t,n)-threshold based secret image sharing schemes, there exists a problem that the secret image can be reconstructed when an arbitrary attacker becomes aware of t secret image pieces, or t participants are malicious collusion. It is because that utilizes linear combination polynomial arithmetic operation. In order to overcome the problem, we propose a secret image sharing scheme using matrix decomposition and adversary structure. In the proposed scheme, there is no reconstruction of the secret image even when an arbitrary attacker become aware of t secret image pieces. Also, we utilize a simple matrix decomposition operation in order to improve the security of the secret image. In experiments, we show that performances of embedding capacity and image distortion ratio of the proposed scheme are superior to previous schemes.