• Title/Summary/Keyword: 블록 기반 추출

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Streaming Decision Tree for Continuity Data with Changed Pattern (패턴의 변화를 가지는 연속성 데이터를 위한 스트리밍 의사결정나무)

  • Yoon, Tae-Bok;Sim, Hak-Joon;Lee, Jee-Hyong;Choi, Young-Mee
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.1
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    • pp.94-100
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    • 2010
  • Data Mining is mainly used for pattern extracting and information discovery from collected data. However previous methods is difficult to reflect changing patterns with time. In this paper, we introduce Streaming Decision Tree(SDT) analyzing data with continuity, large scale, and changed patterns. SDT defines continuity data as blocks and extracts rules using a Decision Tree's learning method. The extracted rules are combined considering time of occurrence, frequency, and contradiction. In experiment, we applied time series data and confirmed resonable result.

Warning Classification Method Based On Artificial Neural Network Using Topics of Source Code (소스코드 주제를 이용한 인공신경망 기반 경고 분류 방법)

  • Lee, Jung-Been
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.11
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    • pp.273-280
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    • 2020
  • Automatic Static Analysis Tools help developers to quickly find potential defects in source code with less effort. However, the tools reports a large number of false positive warnings which do not have to fix. In our study, we proposed an artificial neural network-based warning classification method using topic models of source code blocks. We collect revisions for fixing bugs from software change management (SCM) system and extract code blocks modified by developers. In deep learning stage, topic distribution values of the code blocks and the binary data that present the warning removal in the blocks are used as input and target data in an simple artificial neural network, respectively. In our experimental results, our warning classification model based on neural network shows very high performance to predict label of warnings such as true or false positive.

Feature-based Object Tracking using an Active Camera (능동카메라를 이용한 특징기반의 물체추적)

  • 정영기;호요성
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.3
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    • pp.694-701
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    • 2004
  • In this paper, we proposed a feature-based tracking system that traces moving objects with a pan-tilt camera after separating the global motion of an active camera and the local motion of moving objects. The tracking system traces only the local motion of the comer features in the foreground objects by finding the block motions between two consecutive frames using a block-based motion estimation and eliminating the global motion from the block motions. For the robust estimation of the camera motion using only the background motion, we suggest a dominant motion extraction to classify the background motions from the block motions. We also propose an efficient clustering algorithm based on the attributes of motion trajectories of corner features to remove the motions of noise objects from the separated local motion. The proposed tracking system has demonstrated good performance for several test video sequences.

Block-based Color Image Segmentation Using Cylindrical Metric (Cylindrical metric을 사용한 블록기반 컬러 영상 분할)

  • Nam Hyeyoung;Kim Boram;Kim Wookhyun
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.3 s.303
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    • pp.7-14
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    • 2005
  • In this paper we proposed the block-based color image segmentation method using the cylindrical metric to solve the problems such as long processing time and over segmentation due to noise and texture properties in the conventional methods. In the proposed method we define the new similarity function and the merge condition between regions to merge initial regions with the same size considering the color and texture properties of chromatic and achromatic regions which is defined according to the HSI color values, and we continue to merge boundary blocks into the adjacent region already segmented to maintain edges until the size of block is one. In the simulation results the proposed method is better than the conventional methods in the evaluation of the segmented regions of texture and edge region, and we found that the processing time is decreased by factor of two in the proposed method.

Framework for Building Reusable Design Systems (재사용 가능한 디자인 시스템 구축을 위한 프레임워크)

  • Lee, Young-Ju
    • Journal of Digital Convergence
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    • v.19 no.1
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    • pp.343-348
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    • 2021
  • This study investigated the method of constructing and combining blocks based on the atomic design system in order to propose a framework for rescue of a reusable design system. For that, I first looked at the necessity of a design system and examples of snow white, skeuomorphic design, flat design, and material design. In addition, molecules, atoms, organisms, templates and pages of atomic design using the principles of chemistry as metaphors were defined through literature studies. In order to implement a new framework, an interface inventory was constructed, and among them, font, color, image and control elements were extracted as core visual elements, and guidelines were defined, and molecular elements were classified and composed of atoms based on them. Blocks are constructed in the form of blocks based on the design pattern most used in the content inventory, and the framework is constructed to implement a layout based on a visual grid and design a page through a combination of blocks. The significance of this paper is that the new framework helps team consistency and collaboration by reusing blocks and supports file sharing and updating.

GNUnet improvenemt for anonymity supporing in large multimedia file (대형 멀티미디어 파일의 익명성 지원을 위한 수정 GNUnet)

  • Lee Myoung-Hoon;Park Byung-Yeon;Jo In-June
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2006.05a
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    • pp.81-90
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    • 2006
  • The GNUnet proposed a file encoding method by 1KB block size to support anonimity of files, decentralizes encoded block to peers through unstructed mode and original data decoding method a block searching or encoded blocks. but, the encoding and block decentralizing method with $600\sim700MB$ large multimedia file appered two problems. First problem, it need addition R block and I block, which make about 4% of storage resource. Second problem, unstructured model added network load by broadcasting decentralizing method. Third problem, The critical point of keyword search function. This paper suggest variable encoding block size and structured model by block decentralizing solution. Suggested encoding method reduced block request supplementary block generation from 4% to 1%, network load by proposal structured model sending answer through dedicated peer to decentralize block and we defined content-based keyword and identifier of sharing file.

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Water body extraction using block-based image partitioning and extension of water body boundaries (블록 기반의 영상 분할과 수계 경계의 확장을 이용한 수계 검출)

  • Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.32 no.5
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    • pp.471-482
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    • 2016
  • This paper presents an extraction method for water body which uses block-based image partitioning and extension of water body boundaries to improve the performance of supervised classification for water body extraction. The Mahalanobis distance image is created by computing the spectral information of Normalized Difference Water Index (NDWI) and Near Infrared (NIR) band images over a training site within the water body in order to extract an initial water body area. To reduce the effect of noise contained in the Mahalanobis distance image, we apply mean curvature diffusion to the image, which controls diffusion coefficients based on connectivity strength between adjacent pixels and then extract the initial water body area. After partitioning the extracted water body image into the non-overlapping blocks of same size, we update the water body area using the information of water body belonging to water body boundaries. The update is performed repeatedly under the condition that the statistical distance between water body area belonging to water body boundaries and the training site is not greater than a threshold value. The accuracy assessment of the proposed algorithm was tested using KOMPSAT-2 images for the various block sizes between $11{\times}11$ and $19{\times}19$. The overall accuracy and Kappa coefficient of the algorithm varied from 99.47% to 99.53% and from 95.07% to 95.80%, respectively.

Branch Algorithm for Phoneme Segmentation in Korean Speech Recognition System (한국어 음성인식 시스템에서 음소 경계 검출을 위한 Branch 알고리즘)

  • 서영완;한승진;장흥종;이정현
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.04b
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    • pp.357-359
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    • 2000
  • 음소 단위로 구축된 음성 데이터는 음성인식, 합성 및 분석 등의 분야에서 매우 중요하다. 일반적으로 음소는 유성음과 무성음으로 구분되어 진다. 이러한 유성음과 무성음은 많은 특징적 차이가 있지만, 기존의 음소 경계추출 알고리즘은 이를 고려하지 않고 시간 축을 기준으로 이전 프레임과 매개변수 (스펙트럼) 비교만을 통하여 음소의 경계를 결정한다. 본 논문에서는 음소 경계 추출을 위하여 유성음과 무성음의 특징적 차이를 고려한 블록기반의 Branch 알고리즘을 설계하였다. Branch 알고리즘을 사용하기 위한 스펙트럼 비교 방법은 MFCC(Mel-Frequency Cepstrum Coefficient)를 기반으로 한 거리 측정법을 사용하였고, 유성음과 무성음의 구분은 포만트 주파수를 이용하였다. 실험 결과 3~4음절 고립단어를 대상으로 약 78%의 정확도를 얻을수 있었다.

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A Hybrid System for Extracting Camera Motion from Average Projected Image (평균값을 이용한 통합형 카메라 동작 추출 시스템 개발)

  • Han, Kyu-Seo;Lee, Jae-Yeon;Jeong, Se-Yoon;Bae, Young-Lae
    • Proceedings of the Korea Information Processing Society Conference
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    • 2001.10a
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    • pp.777-780
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    • 2001
  • 동영상 검색 및 관리 기술의 필요성 증가에 따라 동영상 검색 기법들이 제안되고 있으며, 특히 내용 기반 검색 기법에 대두되고 있다. 본 논문에서는 내용 기반 요소중의 하나인 카메라 동작 검출을 위한 시스템을 제안한다. 본 시스템은 영상의 평균값을 이용하여 제작된 투영 영상상에서 추출된 edge 의 방향 성분으로 구성된 optical flow 에 따라 적절한 카메라 동작을 검출한다. 효과적인 카메라 동작 요소 검출을 위하여 평균값으로 구성된 투영 영상을 검출하고자 하는 카메라 동작 요소에 따라 달리 제작한다. 투영 영상은 전체적인 영상에 대하여 제작하는 방법과 sub-block 으로 나눈 영상에 따라 각 블록별로 제작하는 방법으로 나누어진다.

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A High Speed Road Lane Detection based on Optimal Extraction of ROI-LB (관심영역(ROI-LB)의 최적 추출에 의한 차선검출의 고속화)

  • Cheong, Cha-Keon
    • Journal of Broadcast Engineering
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    • v.14 no.2
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    • pp.253-264
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    • 2009
  • This paper presents an algorithm, aims at practical applications, for the high speed processing and performance enhancement of lane detection base on vision processing system. As a preprocessing for high speed lane detection, the vanishing line estimation and the optimal extraction of region of interest for lane boundary (ROI-LB) can be processed to reduction of detection region in which high speed processing is enabled. Image feature information is extracted only in the ROI-LB. Road lane is extracted using a non-parametric model fitting and Hough transform within the ROI-LB. With simultaneous processing of noise reduction and edge enhancement using the Laplacian filter, the reliability of feature extraction can be increased for various road lane patterns. Since outliers of edge at each block can be removed with clustering of edge orientation for each block within the ROI-LB, the performance of lane detection can be greatly improved. The various real road experimental results are presented to evaluate the effectiveness of the proposed method.