• Title/Summary/Keyword: Local quantization

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Novelty Detection using SOM-based Methods (자기구성지도 기반 방법을 이용한 이상 탐지)

  • Lee, Hyeong-Ju;Jo, Seong-Jun
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2005.05a
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    • pp.599-606
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    • 2005
  • Novelty detection involves identifying novel patterns. They are not usually available during training. Even if they are, the data quantity imbalance leads to a low classification accuracy when a supervised learning scheme is employed. Thus, an unsupervised learning scheme is often employed ignoring those few novel patterns. In this paper, we propose two ways to make use of the few available novel patterns. First, a scheme to determine local thresholds for the Self Organizing Map boundary is proposed. Second, a modification of the Learning Vector Quantization learning rule is proposed so that allows one to keep codebook vectors as far from novel patterns as possible. Experimental results are quite promising.

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A Study on The Coarse-to-fine Extraction Method of function Patterns by using The Dynamic Quantization of Parameter Space (매개변수공간의 동적 분할 방법에 의한 함수패턴의 단계적 분석 추출에 관한 연구)

  • 김민환;황희영
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.36 no.8
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    • pp.594-602
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    • 1987
  • This paper proposes a new method of reducing the processing time and the size of consummimg memories in Hough transform. In this method, only the functional patterns are considered. The candidate points which are accumulated into the parameter space are computed in a many-to-one fashion and the parameter space is quantized dynamically to maintain a fine precision where it is needed. And a coarse-to-fine extraction method is used to reduce the processing time. The many-to-one fashional computation results in a relatively high-densed accumulation of candidate points around the parameter points corresponding to the image patterns in the image space. So, the dynamic quantization procedure can be simplified and the local maxima can be determined easily. And more effective reduction can be obtained as the dimension of parameter space is increased.

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A Study on Speech Recognition using GAVQ(Genetic Algorithms Vector Quantization) (GAVQ를 이용한 음성인식에 관한 연구)

  • Lee, Sang-Hee;Lee, Jae-Kon;Jeong, Ho-Kyoun;Kim, Yong-Yun;Nam, Jae-Sung
    • Journal of Industrial Technology
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    • v.19
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    • pp.209-216
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    • 1999
  • In this paper, we proposed a modofied genetic algorithm to minimize misclassification rate for determining the codebook. Genetic algorithms are adaptive methods which may be used solve search and optimization problems based on the genetic processes of biological organisms. But they generally require a large amount of computation efforts. GAVQ can choose the optimal individuals by genetic operators. The position of individuals are optimized to improve the recognition rate. The technical properties of this study is that prevents us from the local minimum problem, which is not avoidable by conventional VQ algorithms. We compared the simulation result with Matlab using phoneme data. The simulation results show that the recognition rate from GAVQ is improved by comparing the conventional VQ algorithms.

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Adaptive Watermarking Using Successive Subband Quantization and Perceptual Model Based on Mukiwavelet Transform (멀티웨이브릿 변환 기반에서 연속 부대역 양자화 및 지각 모델을 이용한 적응 워터마킹 기술)

  • 권기룡;강균호;조영웅;문광석;이준재
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.121-124
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    • 2002
  • This paper presents an adaptive digital image watermarking scheme that uses successive subband quantization (SSQ) and perceptual modeling. Our approach performs a multiwavelet transform to determine the local image properties optimal and the watermark embedding location. The multiwavelet used in this paper is the DGHM multiwavelet with approximation order 2 to reduce artifacts in the reconstructed image. A watermark is embedded into the perceptually significant coefficients (PSC) of the image in each subband. The PSCs in high frequency subbands are selected by setting the thresholds to one half of the largest coefficient in each subband. After the PSCs in each subband are selected, a perceptual model is combined with a stochastic approach based on the noise visibility function to produce the final watermark.

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Terrain Classification Using Three-Dimensional Co-occurrence Features (3차원 Co-occurrence 특징을 이용한 지형분류)

  • Jin Mun-Gwang;Woo Dong-Min;Lee Kyu-Won
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.52 no.1
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    • pp.45-50
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    • 2003
  • Texture analysis has been efficiently utilized in the area of terrain classification. In this application features have been obtained in the 2D image domain. This paper suggests 3D co-occurrence texture features by extending the concept of co-occurrence to 3D world. The suggested 3D features are described using co-occurrence histogram of digital elevations at two contiguous position as co-occurrence matrix. The practical construction of co-occurrence matrix limits the number of levels of digital elevation. If the digital elevation is quantized into the number of levels over the whole DEM(Digital Elevation Map), the distinctive features can not be obtained. To resolve the quantization problem, we employ local quantization technique which preserves the variation of elevations. Experiments has been carried out to verify the proposed 3D co-occurrence features, and the addition of the suggested features significantly improves the classification accuracy.

HEISENBERG GROUPS - A UNIFYING STRUCTURE OF SIGNAL THEORY, HOLOGRAPHY AND QUANTUM INFORMATION THEORY

  • Binz, Ernst;Pods, Sonja;Schempp, Walter
    • Journal of applied mathematics & informatics
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    • v.11 no.1_2
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    • pp.1-57
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    • 2003
  • Vector fields in three-space admit bundles of internal variables such as a Heisenberg algebra bundle. Information transmission along field lines of vector fields is described by a wave linked to the Schrodinger representation in the realm of time-frequency analysis. The preservation of local information causes geometric optics and a quantization scheme. A natural circle bundle models quantum information visualized by holographic methods. Features of this setting are applied to magnetic resonance imaging.

Fast Local Indoor Map Building Using a 2D Laser Range Finder (2차원 레이저 레이진 파이더를 이용한 빠른 로컬 실내 지도 제작)

  • Choi, Ung;Koh, Nak-Yong;Choi, Jeong-Sang
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 1999.10a
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    • pp.99-104
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    • 1999
  • This paper proposes an efficient method constructing a local map using the data of a scanning laser range finder. A laser range finder yields distance data of polar form, that is, distance data corresponding to every scanning directions. So, the data consists of directional angle and distance. We propose a new method to find a line fitting with a set of such data. The method uses Log-Hough Transformation. Usually, map building from these data requires some transformations between different coordinate systems. The new method alleviates such complication. Also, the method simplifies computation for line recognition and eliminates the slope quantization problems inherent in the classical Cartesian Hough transform method. To show the efficiency of the proposed method, it is applied to find a local map using the data from a laser range finder PLS(Proximity Laser Scanner, made by SICK).

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Color Image Quantization Using Local Region Block in RGB Space (RGB 공간상의 국부 영역 블럭을 이용한 칼라 영상 양자화)

  • 박양우;이응주;김기석;정인갑;하영호
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1995.06a
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    • pp.83-86
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    • 1995
  • Many image display devices allow only a limited number of colors to be simultaneously displayed. In displaying of natural color image using color palette, it is necessary to construct an optimal color palette and map each pixel of the original image to a color palette with fast. In this paper, we proposed the clustering algorithm using local region block centered one color cluster in the prequantized 3-D histogram. Cluster pairs which have the least distortion error are merged by considering distortion measure. The clustering process is continued until to obtain the desired number of colors. Same as the clustering process, original color image is mapped to palette color via a local region block centering around prequantized original color value. The proposed algorithm incorporated with a spatial activity weighting value which is smoothing region. The method produces high quality display images and considerably reduces computation time.

Adaptive Watermarking Using Successive Subband Quantization and Perceptual Model Based on Multiwavelet Transform Domain (멀티웨이브릿 변환 영역 기반의 연속 부대역 양자화 및 지각 모델을 이용한 적응 워터마킹)

  • 권기룡;이준재
    • Journal of Korea Multimedia Society
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    • v.6 no.7
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    • pp.1149-1158
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    • 2003
  • Content adaptive watermark embedding algorithm using a stochastic image model in the multiwavelet transform is proposed in this paper. A watermark is embedded into the perceptually significant coefficients (PSCs) of each subband using multiwavelet transform. The PSCs in high frequency subband are selected by SSQ, that is, by setting the thresholds as the one half of the largest coefficient in each subband. The perceptual model is applied with a stochastic approach based on noise visibility function (NVF) that has local image properties for watermark embedding. This model uses stationary Generalized Gaussian model characteristic because watermark has noise properties. The watermark estimation use shape parameter and variance of subband region. it is derive content adaptive criteria according to edge and texture, and flat region. The experiment results of the proposed watermark embedding method based on multiwavelet transform techniques were found to be excellent invisibility and robustness.

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A Rotation Invariant Image Retrieval with Local Features

  • You, Hee-Jun;Shin, Dae-Kyu;Kim, Dong-Hoon;Kim, Hyun-Sool;Park, Sang-Hui
    • International Journal of Control, Automation, and Systems
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    • v.1 no.3
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    • pp.332-338
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    • 2003
  • Content-based image retrieval is the research of images from database, that are visually similar to given image examples. Gabor functions and Gabor filters are regarded as excellent methods for feature extraction and texture segmentation. However, they have a disadvantage not to perform well in case of a rotated image because of its direction-oriented filter. This paper proposes a method of extracting local texture features from blocks with central interest points detected in an image and a rotation invariant Gabor wavelet filter. We also propose a method of comparing pattern histograms of features classified by VQ (Vector Quantization) among images.