• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.5
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• pp.550-558
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• 1988

This paper presents laplacian pyramid vector quantization (LPVQ) approach in which a vector quantizer is used to encode a series of quasi-bandpassed images generated by the laplacian pyramid processing. Performance of the LPVQ is compared to those of DCT domain methods at the same bit rate via computer simulations. Experimental results show that the PSNR's (peak signal-to-noise ratio) for the LPVQ are almost the same as those of the DCT based methods. However, subjective study indicates the LPVQ obtains slightly higher scores than the DCT based techniques.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.3
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• pp.213-224
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• 1992

An encoding technique based on region splitting and vector quantization is proposed for the lower level Laplacian pyramid images. The lower level Laplacian pyramid images have lower variance than higher levels but a great influence on compression ration due to large spatial area. And so from data compression viewpoint, we subdivide them with variance thresholding into two regions such as one called : flat region” and the other “edge region”, and encode the flat region with its mean value and the edge region as vector quantization method. The edge region can be reproduced faithfully and significant improvement on compression ratio can be accomplished with a little degradation of PSNR in spite of the effect of large flat region since the codebook used is generated from the edge region only on from the entire image including the flat region. It can be verified by computer simulation results that proposed method is more efficient in compression ratio and processing time than the conventional encoding technique of vector quantization.

• Journal of Broadcast Engineering
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• v.2 no.2
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• pp.136-145
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• 1997

As a 3D mesh model consists of a lot of vertices and polygons and each vertex position is represented by three 32 bit floating-point numbers in a 3D coordinate, the amount of data needed for representing the model is very excessive. Thus, in order to store and/or transmit the 3D model efficiently, a 3D model compression is necessarily required. In this paper, a 3D model compression method using PRVQ (predictive residual vector quantization) is proposed. Its underlying idea is based on the characteristics such as high correlation between the neighboring vertex positions and the vectorial property inherent to a vertex position. Experimental results show that the proposed method obtains higher compression ratio than that of the existing methods and has the advantage of being capable of transmitting the vertex position data progressively.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.88-98
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• 2011

Recently, according as the importance of GIS(geography information system) database security is embossed, much researches had been achieved about GIS network security. But most such researches are weak against sourceful illegal reproductions and distributions of GIS vector data map. In this paper, we proposed an efficient layer unit contents based partial encryption technique in the vector map compression domain to prevent illegal distributions and unauthorized accesses. This method achieves a partial encryption about each central coordinate and directional parameters of a MCA(minimum coding attribute) that is created at the vector map compression processing in the vector space. First, the position encryption is applied as permutating randomly the center coordinate of each record that is minimum unit of vector map shape. And second, the direction encryption that changing shapes of vector map topography is applied as encrypting the direction of vertices's coordinates of each record. In experimental results, we confirmed that our proposed method can encipher the large volumed vector map data effectively in low computational complexity. Also, we could minimize the decline of compression efficiency that occurred by conventional contents based encryption schemes using AES or DES algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2572-2589
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• 2014

Reversible data hiding is a technique for recovering original images without any distortion after secret data are extracted from the image. The technique continues to attract attention from many researchers. In this paper, we introduce a new reversible data hiding scheme based on the adjacent index differences of vector quantization (VQ) indices. The proposed scheme exploits the differences between two adjacent indices to embed secret data. Experimental results show that our scheme can achieve a lower compression rate than an earlier scheme by Yang and Lin. Our scheme's average compression rate, 0.44 bpp, outperforms that of Yang and Lin's scheme, which averages 0.53 bpp. Moreover, the embedding capacity of our scheme can rise to 1.45 bpi, which also is superior to that of Chang et al.'s scheme [35] (1.00 bpi)Yang and Lin's scheme [27] (0.91 bpi) as well as Chang et al.'s scheme [26] (0.74 bpi).

• Journal of Multimedia Information System
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• v.6 no.2
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• pp.91-98
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• 2019

Many researchers have attempted to recognize three-dimensional faces using feature points extracted from two-dimensional facial photographs. However, due to the limit of flat photographs, it is very difficult to recognize faces rotated more than 15 degrees from original feature points extracted from the photographs. As such, it is difficult to create an algorithm to recognize faces in multiple angles. In this paper, it is proposed a new algorithm to recognize three-dimensional face recognition based on feature points extracted from a flat photograph. This method divides into six feature point vector zones on the face. Then, the vector value is compressed and expanded according to the rotation angle of the face to recognize the feature points of the face in a three-dimensional form. For this purpose, the average of the compressibility and the expansion rate of the face data of 100 persons by angle and face zone were obtained, and the face angle was estimated by calculating the distance between the middle of the forehead and the tail of the eye. As a result, very improved recognition performance was obtained at 30 degrees of rotated face angle.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.37-44
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• 2009

Digital watermarking is a technology for preventing illegal copying, for protecting intellectual property rights and copyrights, and for suggesting grounds of the ownership by inserting watermarks into digital contents. Generally speaking, watermarking techniques cannot escape from data distortion and quality degradation due to the watermark insertion. In order to overcome the shortcoming, zero-watermarking techniques which do not change the original data have been proposed recently. This paper proposes CSMVQ(Chaotic SMVQ), a zero-watermarking system for SMVQ(Side Match Vector Quantization) which shows better compression ratio and quality and less blocking effect than VQ(Vector Quantization). In SMVQ, compression progresses from left top to right bottom in order to use the information of the two neighbor blocks, so it is impossible to insert watermarks chaotically. In the process of encoding, CSMVQ dynamically considers the information of the (1 to 4) neighbor blocks already encoded. Therefore, watermark can be inserted into digital contents in chaotic way. Experimental results show that the image quality compressed by CSMVQ is better than that of SMVQ and the inserted watermark is robust against some common attacks.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.9
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• pp.80-87
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• 1996

This paper proposes an image compression algorithm that adopts projection scheme on wavelet transform domain of image signal. Wavelet decomposed image is encoded by the result of projection along one direction out of eight which approximates the coefficients most closely to the originally transformed coefficients. These projectrion data are vector quantized using separate codebooks depending on the decomposition level and orientation of decomposed of image. Experimental results reveals that proposed scheme shows excellent performance in PSNR manner and also shows good subjective quality.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.467-470
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• 2000

Vector quantization (VQ) is widely used in many high-quality and high-rate data compression applications such as speech coding, audio coding, image coding and video coding. When the size of a VQ codebook is large, the computational complexity for the full codeword search method is a significant problem for many applications. A number of complexity reduction algorithms have been proposed and investigated using such properties of the codebook as the triangle inequality. This paper proposes a new structured VQ search algorithm that is based on a multi-stage structure for searching for the best codeword. Even using only two stages, a significant complexity reduction can be obtained without any loss of quality.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1200-1202
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• 2003

Satellite and aerial images are very useful means to monitor ecological and environmental situation. Nowadays more and more officials at Ministry of Environment in Korea need to access and use these image data through networks like internet or intranet. However it is very hard to manage and service these image data through internet or intranet, because of its size problem. In this paper very large image data service system for Ministry of Environment is constructed on web environment using image compression and web based image processing technology. Through this system, not only can officials in Ministry of Environment access and use all the image data but also can achieve several image processing effects on web environment. Moreover officials can retrieve attribute information from vector GIS data that are also integrated with the system.