• Title/Summary/Keyword: Vector compression

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Segmentation of the Lip Region by Color Gamut Compression and Feature Projection (색역 압축과 특징치 투영을 이용한 입술영역 분할)

  • Kim, Jeong Yeop
    • Journal of Korea Multimedia Society
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    • v.21 no.11
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    • pp.1279-1287
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    • 2018
  • In this paper, a new type of color coordinate conversion is proposed as modified CIEXYZ from RGB to compress the color gamut. The proposed segmentation includes principal component analysis for the optimal projection of a feature vector into a one-dimensional feature. The final step adopted for lip segmentation is Otsu's threshold for a two-class problem. The performance of the proposed method was better than that of conventional methods, especially for the chromatic feature.

A Technical Analysis on Deep Learning based Image and Video Compression (딥 러닝 기반의 이미지와 비디오 압축 기술 분석)

  • Cho, Seunghyun;Kim, Younhee;Lim, Woong;Kim, Hui Yong;Choi, Jin Soo
    • Journal of Broadcast Engineering
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    • v.23 no.3
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    • pp.383-394
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    • 2018
  • In this paper, we investigate image and video compression techniques based on deep learning which are actively studied recently. The deep learning based image compression technique inputs an image to be compressed in the deep neural network and extracts the latent vector recurrently or all at once and encodes it. In order to increase the image compression efficiency, the neural network is learned so that the encoded latent vector can be expressed with fewer bits while the quality of the reconstructed image is enhanced. These techniques can produce images of superior quality, especially at low bit rates compared to conventional image compression techniques. On the other hand, deep learning based video compression technology takes an approach to improve performance of the coding tools employed for existing video codecs rather than directly input and process the video to be compressed. The deep neural network technologies introduced in this paper replace the in-loop filter of the latest video codec or are used as an additional post-processing filter to improve the compression efficiency by improving the quality of the reconstructed image. Likewise, deep neural network techniques applied to intra prediction and encoding are used together with the existing intra prediction tool to improve the compression efficiency by increasing the prediction accuracy or adding a new intra coding process.

STRUCTURED CODEWORD SEARCH FOR VECTOR QUANTIZATION (백터양자화가의 구조적 코더 찾기)

  • 우홍체
    • 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.

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A Kernel Approach to Discriminant Analysis for Binary Classification

  • Shin, Yang-Kyu
    • Journal of the Korean Data and Information Science Society
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    • v.12 no.2
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    • pp.83-93
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    • 2001
  • We investigate a kernel approach to discriminant analysis for binary classification as a machine learning point of view. Our view of the kernel approach follows support vector method which is one of the most promising techniques in the area of machine learning. As usual discriminant analysis, the kernel method can discriminate an object most likely belongs to. Moreover, it has some advantage over discriminant analysis such as data compression and computing time.

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Object-based Stereo Sequence Coding using Disparity and Motion Vector Relationship (변이-움직임 벡터의 상관관계를 이용한 객체기반 스테레오 동영상 부호화)

  • 박찬희;손광훈
    • Journal of Broadcast Engineering
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    • v.7 no.3
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    • pp.238-247
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    • 2002
  • In this paper, we propose an object-based stereo sequence compression technique using disparity-motion vector relationship. The proposed method uses the coherence of motion vectors and disparity vectors in the left and right Image sequences. After two motion vectors and one disparity vector ate computed using FBMA(Fixed Block Matching Algorithm), the disparity vector of the current stereoscopic pall is computed by disparity-motion vector relationship with vectors which are previously estimated. Moreover, a vector regularization technique is applied in order to obtain reliable vectors. For an object-based coding. the object is defined and coded in terms of layers of VOP such as in MPEG-4. we present a method using disparity and motion vector relationship for extending two-frame compensation into three-frame compensation method for prediction coding of B-VOP. The proposed algorithm shows a high performance when comparing with a conventional method.

Adaptive Interleaved Motion Vector Coding using Motion Characteristics (움직임 특성을 이용한 적응적 교차 움직임 벡터 부-복호화)

  • Won, Kwang-Hyun;Yang, Jung-Youp;Park, Dae-Yun;Jeon, Byeung-Woo
    • Journal of Broadcast Engineering
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    • v.16 no.2
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    • pp.372-383
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    • 2011
  • This paper proposes an improved design of an interleaved motion vector coding scheme with flexibility in predictive motion vector component by exploiting motion characteristics. It can use component-wise adaptive motion vector predictor based on the utility of spatial and temporal motion field without any signaling bit for indicating decoder of the selected predictive motion vector component. Experiment with test video data shows about 1.99% (max 8.71%) bit rate reduction compared to the conventional H.264/AVC method.

Design of LZW-Bit Vector Compression Algorithm for Effective BiometricData Transmission in M2M Environment (M2M기반 효율적인 생체데이터 전송을 위한 LZW-BitVector 압축 알고리즘 설계)

  • Kang, San;Park, Seok-Cheon;Park, Jung-Hwan
    • Proceedings of the Korea Information Processing Society Conference
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    • 2015.04a
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    • pp.652-654
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    • 2015
  • 최근 ICT융합 기술의 비약적인 발전에 따라 소형 휴대가 가능한 다양한 종류의 생체신호 측정센서의 출현으로 유헬스케어 관련 기술이 비약적으로 발전하게 되면서, 실시간으로 발생하는 생체데이터에 대한 효율적인 처리가 중요하게 되었다. 따라서 본 논문에서는 M2M기반에서 발생되는 생체데이터의 효율적인 전송을 위해 LZW(Lempel-Ziv-Welch) 압축 알고리즘과, BitVector압축 알고리즘을 결합한 LZW-BitVector 압축 알고리즘을 제안한다.

A Fast Sub-pixel Motion Estimation Method for H.264 Video Compression (H.264 동영상 압축을 위한 부 화소 단위에서의 고속 움직임 추정 방법)

  • Lee, Yun-Hwa;Choi, Myung-Hoon;Shin, Hyun-Chul
    • Journal of KIISE:Software and Applications
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    • v.33 no.4
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    • pp.411-417
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    • 2006
  • Motion Estimation (ME) is an important part of video coding process and it takes the largest amount of computation in video compression. Half-pixel and quarter-pixel motion estimation can improve the video compression rate at the cost of higher computational complexity In this paper, we suggest a new efficient low-complexity algorithm for half-pixel and quarter pixel motion estimation. It is based on the experimental results that the sum of absolute differences(SAD) shows parabolic shape and thus can be approximated by using interpolation techniques. The sub-pixel motion vector is searched from the minimum SAD integer-pixel motion vector. The sub-pixel search direction is determined toward the neighboring pixel with the lowest SAD among 8 neighbors. Experimental results show that more than 20% reduction in computation time can be achieved without affecting the quality of video.

A Lossless Vector Data Compression Using the Hybrid Approach of BytePacking and Lempel-Ziv in Embedded DBMS (임베디드 DBMS에서 바이트패킹과 Lempel-Ziv 방법을 혼합한 무손실 벡터 데이터 압축 기법)

  • Moon, Gyeong-Gi;Joo, Yong-Jin;Park, Soo-Hong
    • Spatial Information Research
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    • v.19 no.1
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    • pp.107-116
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    • 2011
  • Due to development of environment of wireless Internet, location based services on the basis of spatial data have been increased such as real time traffic information as well as CNS(Car Navigation System) to provide mobile user with route guidance to the destination. However, the current application adopting the file-based system has limitation of managing and storing the huge amount of spatial data. In order to supplement this challenge, research which is capable of managing large amounts of spatial data based on embedded database system is surely demanded. For this reason, this study aims to suggest the lossless compression technique by using the hybrid approach of BytePacking and Lempel-Ziv which can be applicable in DBMS so as to save a mass spatial data efficiently. We apply the proposed compression technique to actual the Seoul and Inchcon metropolitan area and compared the existing method with suggested one using the same data through analyzing the query processing duration until the reconstruction. As a result of comparison, we have come to the conclusion that suggested technique is far more performance on spatial data demanding high location accuracy than the previous techniques.

Adaptive Video Watermarking Using Half-cell Motion Vector (반화소 움직임 벡터를 이용한 적응적 비디오워터마킹)

  • Shinn Brian-B.;Kim Min-Yeong;D Khongorzul;Lee In-Sung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.7
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    • pp.1214-1221
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    • 2006
  • Header compression scheme is suggested as a solution to reduce the inefficient overhead of general packet stream data. Especially, it is shown that there are more overhead rate for real-time media stream links such as voice because of its short payload size, and it is possible to get higher bandwidth efficiency using the header compression scheme. There are two kinds of error recovery in header compression such as Periodic Header Refresh(PHR) and Header Request(HR) schemes. In this paper, we analyze the performance of these two compression recovery schemes, and some results such as the overhead rate, bandwidth gain and bandwidth efficiency(BE) are presented.