• Journal of Advanced Navigation Technology
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• v.12 no.3
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• pp.273-279
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• 2008

In this paper, we proposed a watermarking algorithm by using difference matrix between successive blocks in the transform domain. In the preprocessing, original image is decomposed with 1-level sub-bands by DWT. Then, all sub-bands which are excepted the low-frequency bands are set to normalize and make a reference image after transforming inverse DWT. The statistic variance of successive blocks between the original image and the reference image are calculated and finally, watermark is embedded considering the local characteristic with respect to the high-frequence components. Experimental results showed that the proposed approach is robust and better invisible in such attacks as filtering, JPEG and noise addition.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.33-36
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• 2003

Principal component analysis (PCA) was used to improve image classification by the unsupervised classification techniques, the K-means. To do this, I selected a Landsat TM scene of Jeju Island, Korea and proposed two methods for PCA： unstandardized PCA (UPCA) and standardized PCA (SPCA). The estimated accuracy of the image classification of Jeju area was computed by error matrix. The error matrix was derived from three unsupervised classification methods. Error matrices indicated that classifications done on the first three principal components for UPCA and SPCA of the scene were more accurate than those done on the seven bands of TM data and that also the results of UPCA and SPCA were better than those of the raw Landsat TM data. The classification of TM data by the K-means algorithm was particularly poor at distinguishing different land covers on the island. From the classification results, we also found that the principal component based classifications had characteristics independent of the unsupervised techniques (numerical algorithms) while the TM data based classifications were very dependent upon the techniques. This means that PCA data has uniform characteristics for image classification that are less affected by choice of classification scheme. In the results, we also found that UPCA results are better than SPCA since UPCA has wider range of digital number of an image.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.741-754
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• 1997

Code matrix is the matrix of which on element and its neighbors are arranged to have a code value. The code matrix was originally designed by the author for developing a vision system but has not been theoretically studied. In this paper some theoretical properties of the code matrix are investigated. The studied characteristics of the code matrix are useful for not only understanding the matrix itself but efficiently restructuring the matrix. A number of transformation functions, which enable the matrix to have different shape, are thus developed based on the investigated properties. The transformation functions are then applied to build a perfectly and uniformly structured square code matrix, which is proven useful in on image processing example. The study in this paper is expected to serve a theoretical background for the application of the code matrix in many areas.

• Journal of the Korean Society of Costume
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• v.55 no.1 s.91
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• pp.151-164
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• 2005

In the modern popular culture, a significant code is not the truth itself but the seeming truth. To fulfill this function, it is a mythology that has a transcendental power to eliminate any doubt and mystery. That is to say, cultural uniqueness is understood as an identical thing through mass communication, and people perceive it as a similar cultural community. In this process, mythology form and accumulate the matrix of mythological meaning by eliminating the difference between the reality and the illusion. Such a matrix forces a meaningless and unconditional truth and practice without any criticism and reconsideration. This paper tries to extract art and cultural characteristics of mythological image through examining the relationship among mythological image, history, and ideology. For this aim, we make use of Roland Barthes' signs and Daniel Boorstin's image as a basic analytical tool. After that we examine the characteristics of mythological image appeared in modern cultural discourses and the relationship between mythological image and modern popular culture. Furthermore, we consider the mythological image expressed in modern fashion, which has the nature of commodity aesthetics.

• Journal of the Korean Mathematical Society
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• v.51 no.5
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• pp.941-953
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• 2014

In this paper, a 2-circular matrix theory is developed, and a concept of spectral radius for biorthogonal wavelet is introduced. We propose a novel design method by minimizing the spectral radius and obtain a wavelet which has better performance than the famous 9-7 wavelet in terms of image compression coding.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2748-2766
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• 2016

Compared with traditional patch-based sparse representation, recent studies have concluded that group-based sparse representation (GSR) can simultaneously enforce the intrinsic local sparsity and nonlocal self-similarity of images within a unified framework. This article investigates an accelerated split Bregman method (SBM) that is based on GSR which exploits image compressive sensing (CS). The computational efficiency of accelerated SBM for the measurement matrix of a partial Fourier matrix can be further improved by the introduction of a fast Fourier transform (FFT) to derive the enhanced algorithm. In addition, we provide convergence analysis for the proposed method. Experimental results demonstrate that accelerated SBM is potentially faster than some existing image CS reconstruction methods.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.9-11
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• 2005

We propose a new content-based image retrieval using a block color co-occurrence matrix (BCCM) and pattern correlogram. In the proposed method, the color feature vectors are extracted by using BCCM that represents the probability of the co-occurrence of two mean colors within blocks. Also the pattern feature vectors are extracted by using pattern correlogram which is combined with spatial correlation of pattern. In the proposed pattern correlogram method. after block-divided image is classified into 48 patterns with respect to the change of the RGB color of the image, joint probability between the same pattern from the surrounding blocks existing at the fixed distance and the center pattern is calculated. Experimental results show that the proposed method can outperform the conventional methods as regards the precision and the size of the feature vector dimension.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.601-604
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• 1999

This Paper proposes the simple and efficient image retrieval algorithm using subregional texture features. In order to retrieve images in terms of its contents, it is required to obtain a precise segmentation. However, it is very difficult and takes a long computing time. Therefore. this paper proposes a simple segmentation method, which is to divide an image into high and low entropy regions by using Picture Information Measure (PIM). Also, in order to describe texture characteristics of each region, this paper suggest six different texture features produced on the basis of co-occurrence matrix. For an image retrieval system, a normalised correlation is adopted as a similarity function, which is not dependent on the range of each texture feature values. Finally, this proposed algorithm is applied to a various images and produces competitive results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.1041-1046
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• 2009

In this paper, we proposed a robust watermark scheme for image based on SVD(Singular Value Transform) and Triplet. First, the original image is decomposed by using 3-level DWT, and then used the singular values changed for embedding and extracting of the watermark sequence in LL3 band. Since the matrix of singular values is not easily altered with various signal processing noises, the embedded watermark sequence has the ability to withstand various signal processing noise attacks. Nevertheless, this method does not guarantee geometric transformation(such as rotation, cropping, etc.) because the geometric transformation changes the matrix size. In this case, the watermark sequence cannot be extracted. To compensate for the above weaknesses, a method which uses the triplet for embedding a barcode image watermark in the middle of frequency band is proposed. In order to generate the barcode image watermark, the pattern of the watermark sequence embedded in a LL3 band is used. According to this method, the watermark information can be extracted from attacked images.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.2
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• pp.1-11
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• 2021

Salt and pepper is a type of impulse noise. It may appear due to an error in the image transmission process and image storage memory. This noise changes the pixel value at any position in the image to 0 (in case of pepper noise) or 255 (in case of salt noise). In this paper, we present an algorithm for SAP noise reduction. The proposed method consists of three steps. In the first step, the location of the SAP noise is detected, and in the second step, the pixel value of the detected location is restored using a weighted average of the surrounding pixel values. In the last step, a reliability matrix around the reconstructed pixels is constructed, and additional correction is performed with a weighted average using this. As a result of the experiment, the proposed method appears to have similar or higher objective and subjective image quality than previous methods for almost all SAP noise ratios.