• Title/Summary/Keyword: vector quantization

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Zero-Watermarking based on Chaotic Side Match Vector Quantization (무질저한 SMVQ 기반의 제로-워터마킹)

  • Kim, Hyung-Do;Park, Chan-Kwon
    • 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.

Image Data Compression using Laplacian Pyramid Processing and Vector Quantization (Laplacian Pyramid Processing과 벡터 양자화 방법을 이용한 영상 데이터 압축)

  • 박광훈;안동순;차일환;윤대희
    • 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.

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An Watermarking Method based on Singular Vector Decomposition and Vector Quantization using Fuzzy C-Mean Clustering (특이치 분해와 Fuzzy C-Mean(FCM) 군집화를 이용한 벡터양자화에 기반한 워터마킹 방법)

  • Lee, Byeong-Hui;Jang, U-Seok;Gang, Hwan-Il
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.11a
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    • pp.267-271
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    • 2007
  • 본 논문은 원본이미지와 은닉이미지의 좋은 압축률과 만족할만한 이미지의 질, 그리고 외부공격에 강인한 이미지은닉의 한 방법으로 특이치 분해와 퍼지 군집화를 이용한 벡터양자화를 이용한 워터마킹 방법을 소개하였다. 실험에서는 은닉된 이미지의 비가시성과 외부공격에 대한 강인성을 증명하였다.

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Medical Image Data Compression Using a Variable Block Size Vector Quantization (가변 블록 벡터양자화를 이용한 의용영상 데타터 압축)

  • 박종규;정회룡
    • Journal of Biomedical Engineering Research
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    • v.10 no.2
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    • pp.173-178
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    • 1989
  • A vector quantization technique using a variable block size was applied to image compression of digitized X -ray films. Whether the size of VQ block should be subdivided or not is determined experimentally by the threshold value. The simulation result shows that the performance of the proposed vector quantizer is suitable for the medical image coding, which is applicable to PACS( Picture Archiving and Communication System).

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A DCT-based hierarcical finite state vector quantization for image coding (영상 부호화를 위한 이산 여현변환 기반의 계층적 유한 상태 벡터 양자화 기법)

  • 남일우;김응성;이근영
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.1
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    • pp.88-95
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    • 1998
  • In this paper, we introduce a new DCT based hierarchical finite state vector quantization. Our proposed scheme uses difference of DCT coefficients to find a representative vector, and classifies image blocks into different hierarchical levels depending on their structural characteristics, and uses different coding rates and different number os state codebooks at each hierarchical levels. As a result, we obtained reconstructed images having satisfiable quality objectively.

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Forward Viterbi Decoder applied LVQ Network (LVQ Network를 적용한 순방향 비터비 복호기)

  • Park Ji woong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.12A
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    • pp.1333-1339
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    • 2004
  • In IS-95 and IMT-2000 systems using variable code rates and constraint lengths, this paper limits code rate 1/2 and constraint length 3 and states the effective reduction of PM(Path Metric) and BM(Branch Metric) memories and arithmetic comparative calculations with appling PVSL(Prototype Vector Selecting Logic) and LVQ(Learning Vector Quantization) in neural network to simplify systems and to decode forwardly. Regardless of extension of constraint length, this paper presents the new Vierbi decoder and the appied algorithm because new structure and algorithm can apply to the existing Viterbi decoder using only uncomplicated application and verifies the rationality of the proposed Viterbi decoder through VHDL simulation and compares the performance between the proposed Viterbi decoder and the existing.

Face Recognition using Vector Quantizer in Eigenspace (아이겐공간에서 벡터 양자기를 이용한 얼굴인식)

  • 임동철;이행세;최태영
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.5
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    • pp.185-192
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    • 2004
  • This paper presents face recognition using vector quantization in the eigenspace of the faces. The existing eigenface method is not enough for representing the variations of faces. For making up for its defects, the proposed method use a clustering of feature vectors by vector quantization in eigenspace of the faces. In the trainning stage, the face images are transformed the points in the eigenspace by eigeface(eigenvetor) and we represent a set of points for each people as the centroids of vector quantizer. In the recognition stage, the vector quantizer finds the centroid having the minimum quantization error between feature vector of input image and centriods of database. The experiments are performed by 600 faces in Faces94 database. The existing eigenface method has minimum 64 miss-recognition and the proposed method has minimum 20 miss-recognition when we use 4 codevectors. In conclusion, the proposed method is a effective method that improves recognition rate through overcoming the variation of faces.

Adaptive subband vector quantization using motion vector (움직임 벡터를 이용한 적응적 부대역 벡터 양자화)

  • 이성학;이법기;이경환;김덕규
    • Proceedings of the IEEK Conference
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    • 1998.06a
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    • pp.677-680
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    • 1998
  • In this paper, we proposed a lwo bit rate subband coding with adaptive vector quantization using the correlation between motion vector and block energy in subband. In this method, the difference between the input signal and the motion compensated interframe prediction signal is decomposed into several narrow bands using quadrature mirror filter (QMF) structure. The subband signals are then quantized by adaptive vector quantizers. In the codebook generating process, each classified region closer to the block value in the same region after the classification of region by the magnitude of motion vector and the variance values of subband block. Because codebook is genrated considering energy distribution of each region classified by motion vector and variance of subband block, this technique gives a very good visual quality at low bit rate coding.

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Multi-level Vector Error Diffusion for Smear Artifact Reduction in the Boundary Regions (경계 영역에서 색 번짐 감소를 위한 멀티레벨 벡터 오차 확산법)

  • 박태용;조양호;김윤태;하영호
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.461-464
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    • 2003
  • This paper proposes the multi-level vector error diffusion for smear artifact reduction in the boundary regions. Smear artifact mainly results from a large accumulation of quantization error. Accordingly, to reduce these artifacts, the proposed method excludes the large quantization error in the error diffusion process by comparing the magnitude of the error vector with predetermined first threshold. In addition, if the vector norm of the difference between the error adjusted input vector and the primary co]or that has minimum vector norm for the error adjusted input vector is larger than second threshold, the error is excluded. As a result, the proposed method reduce smear artifact in the boundary region and produces visually pleasing halftone pattern.

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Automatic Music Summarization Using Vector Quantization and Segment Similarity

  • Kim, Sang-Ho;Kim, Sung-Tak;Kim, Hoi-Rin
    • The Journal of the Acoustical Society of Korea
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    • v.27 no.2E
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    • pp.51-56
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    • 2008
  • In this paper, we propose an effective method for music summarization which automatically extracts a representative part of the music by using signal processing technology. Proposed method uses a vector quantization technique to extract several segments which can be regarded as the most important contents in the music. In general, there is a repetitive pattern in music, and human usually recognizes the most important or catchy tune from the repetitive pattern. Thus the repetition which is extracted using segment similarity is considered to express a music summary. The segments extracted are again combined to generate a complete music summary. Experiments show the proposed method captures the main theme of the music more effectively than conventional methods. The experimental results also show that the proposed method could be used for real-time application since the processing time in generating music summary is much faster than other methods.