• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.474-485
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• 2001

This paper proposes a user-key-based fragile watermarking for detecting image modification. The embedding data in a form of binary image for authentication are inserted to the DCT coefficients of each block of the given image. To minimize possible exposure of being watermarked and the location of insertion, it is proposed to utilize a user-specific key in randomizing those information. Each DCT block hides one bit of data, all of which represent the user-specific authentication data. Experiments with 5 real images demonstrate that the proposed method not only detects whether there is modification or not, but also the actual location of modification with minimal visual deterioration. However, the proposed method has room for improvement against its loss of watermark by an attack of compression by more than 50%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2C
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• pp.100-109
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• 2003

A differential index assignment scheme is proposed for the image encoding system in which a variable-length tree-structured vector quantizer is adopted. Each source vector is quantized into a terminal node of VLTSVQ and each terminal node is represented as a unique binary vector. The proposed index assignment scheme utilizes the correlation between interblocks of the image to increase the compression ratio with the image quality maintained. Simulation results show that the proposed scheme achieves a much higher compression ratio than the conventional one does and that the amount of the bit rate reduction of the proposed scheme becomes large as the correlation of the image becomes large. The proposed encoding scheme can be effectively used to encode R images whose pixel values we, in general, highly correlated with those of the neighbor pixels.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.713-716
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• 2009

In this paper, we propose a vision-based detection of container hole for container location measuring. We use a method for container position using detection of diagonal container holes, because containers have holes that are linked to spreader headblocks. First, we extract images from spreader and detect straight lines to detect container in images using hough transform. Next, proposed method finds positions of cross at the right angles and set candidates of the corner that is linked to spreader headblocks. Finally, this method performs template matching to detect a right corner of containers. Experimental results show that proposed method performed well at detection of container position.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.2
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• pp.207-214
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• 2015

In this paper the independence axiom, one of two principal axioms of axiomatic design theory, is applied to the leveling system development as an design criteria. After functional requirements and corresponding design parameters constitute an initial design matrix for the leveling system, sequence, which is compatible with the independence axiom, of the design parameters of the design matrix is determined and independent components of block leveling system are revealed. As a result of axiomatic design, system configuration related to the design sequence is developed. In order to verify and validate the developed block leveling system, test with real hull block leveling work in site by using total station which is used to acquire three dimensional coordinate of target point is performed. Comparison with measured data and output data from the block leveling system shows the system accuracy is under 1 mm so that the developed system is verified and validated to be used in site.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.169-175
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• 2008

The existing block encryption algorithms have been designed for the encryption key value to be unchanged and applied to the round functions of each block. and enciphered. Therefore, it has such a weak point that the plaintext or encryption key could be easily exposed by differential cryptanalysis or linear cryptanalysis, both are the most powerful methods for decoding block encryption of a round repeating structure. Dynamic cipher has the property that the key-size, the number of round, and the plaintext-size are scalable simultaneously. Dynamic network is the unique network satisfying these characteristics among the networks for symmetric block ciphers. We analyze the strength of Dynamic network for meet-in-the-middle attack, linear cryptanalysis, and differential cryptanalysis. Also, In this paper we propose a new network called Dynamic network for symmetric block ciphers.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.284-289
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• 2008

H.264/AVC among moving picture compression standard is the standard format for high compression rate and reliable video transimission. It generates blocking effects in video due to compressing video using block-based DCT and includes de-blocking filter to reduce blocking effect. Therefore, the filter makes the video over-smoothing and the quality of it is reduced. In this paper, we propose a improved de-blocking filter to solve the demerit. The proposed de-blocking filter redetermine the block boundary strength and apply the comer filtering to eliminate artifacts in low frequency domain. To evaluate the performance, we apply the proposed deblocking filter and exiting method to various video and evaluated the quality of image subjectively and objectively by analyzing the result. The simulation result shows the proposed method preserves the edge of video, reduces blocking effects and improves PSNR than the existing method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.505-513
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• 2004

Most video codecs including the international standards use the block-based hybrid structure for efficient compression. But for low bit-rate applications such as video transmission through wireless channels, the blocking artifacts degrade image qualify seriously. In this paper, we propose an adaptive de-blocking algorithm using characteristics of the block boundaries. Blocking artifacts contain the high frequency components near the block boundaries, therefore the lowpass filtering can remove them. However, simple lowpass filtering results into blurring by removing important information such as edges. To overcome this problem, we determine the modes depending upon the characteristics of pixels adjacent to block boundary then proper filter is applied to each area. Simulation results show that proposed method improves de-blocking performance compared to that of MPEG-4.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.65-79
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• 2003

In general, the extraction and recognition of identifier is very hard work, because the scale or location of identifier is not fixed-form. And, because the provided image is contained by camera, it has some noises. In this paper, we propose methods for automatic detecting edge using canny edge mask. After detecting edges, we extract regions of identifier by detected edge information's. In regions of identifier, we extract each identifier using contour tracking algorithm. The self-generation supervised learning algorithm is proposed for recognizing them, which has the algorithm of combining the enhanced ART1 and the supervised teaming method. The proposed method has applied to the container images. The extraction rate of identifier obtained by using contour tracking algorithm showed better results than that from the histogram method. Furthermore, the recognition rate of the self-generation supervised teaming method based on enhanced ART1 was improved much more than that of the self-generation supervised learning method based conventional ART1.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.15-22
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• 2020

In this paper, we proposed a deep learning based super-resolution method that combines Channel Attention and Spatial Attention feature enhancement methods. It is important to restore high-frequency components, such as texture and features, that have large changes in surrounding pixels during super-resolution processing. We proposed a super-resolution method using feature enhancement that combines Channel Attention and Spatial Attention. The existing CNN (Convolutional Neural Network) based super-resolution method has difficulty in deep network learning and lacks emphasis on high frequency components, resulting in blurry contours and distortion. In order to solve the problem, we used an emphasis block that combines Channel Attention and Spatial Attention to which Skip Connection was applied, and a Residual Block. The emphasized feature map extracted by the method was extended through Sub-pixel Convolution to obtain the super resolution. As a result, about PSNR improved by 5%, SSIM improved by 3% compared with the conventional SRCNN, and by comparison with VDSR, about PSNR improved by 2% and SSIM improved by 1%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.136-144
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• 2010

Two types of informations are used for content-based video copy detection: spatial information and temporal information. The spatial information means content-based image fingerprint. This image fingerprint must have following characteristic. First, Extraction is simple. Second, pairwise independence for random selected two images. At last, Robust for modifications. This paper proposed image fingerprint method for contents based video copy detection. Proposed method's extraction speed is fast because this method's using block average, first order differentiation and second order differentiation that can be calculated add and minus operation. And it has pairwise independence and robust against modifications. Also, proposed method feature makes binary by comparisons and using coarse to fine structure, so it's matching speed is fast. Proposed method is verified by modified image that modified by VCE7's experimental conditions in MPEG7.