• Title, Summary, Keyword: 분할

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MDVC Algorithm for the Improvement of Subdivision Mesh`s Quality (Subdivision Mesh의 품질 향상을 위한 MDVC 알고리즘)

  • 이영건;김창헌
    • Proceedings of the Korean Information Science Society Conference
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    • pp.715-717
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    • 2002
  • 본 논문은 분할 메쉬의 품질을 향상시키기 위해 초기 메쉬의 위상을 최적화 시키는 MDVC(Modified Dynamic Vertex Connectivity) 알고리즘을 제안한다. 분할 메쉬는 초기 메쉬는 초기 메쉬에 연속적인 분할 규칙이 적용된 메쉬로, 초기 메쉬의 위상에 따라 분할 메쉬의 모양과 부드러움이 좌우된다. 본 논문에서 제안하는 MDVC 알고리즘은 초기 메쉬의 위상과 aspect ratio를 개선시키므로, 기존의 분할 메쉬에서 발생하던 뒤틀림 현상을 방지할 수 있고, 초기 메쉬의 규칙점의 개수가 증가되도록 위상정보를 변경시켜 메쉬분할시 부드러움을 개선시킬 수 있다.

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A Novel Segment Extraction and Stereo Matching Technique using Color, Motion and Initial Depth from Depth Camera (컬러, 움직임 정보 및 깊이 카메라 초기 깊이를 이용한 분할 영역 추출 및 스테레오 정합 기법)

  • Um, Gi-Mun;Park, Ji-Min;Bang, Gun;Cheong, Won-Sik;Hur, Nam-Ho;Kim, Jin-Woong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.12C
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    • pp.1147-1153
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    • 2009
  • We propose a novel image segmentation and segment-based stereo matching technique using color, depth, and motion information. Proposed technique firstly splits reference images into foreground region or background region using depth information from depth camera. Then each region is segmented into small segments with color information. Moreover, extracted segments in current frame are tracked in the next frame in order to maintain depth consistency between frames. The initial depth from the depth camera is also used to set the depth search range for stereo matching. Proposed segment-based stereo matching technique was compared with conventional one without foreground and background separation and other conventional one without motion tracking of segments. Simulation results showed that the improvement of segment extraction and depth estimation consistencies by proposed technique compared to conventional ones especially at the static background region.

Intra-Sentence Segmentation using Maximum Entropy Model for Efficient Parsing of English Sentences (효율적인 영어 구문 분석을 위한 최대 엔트로피 모델에 의한 문장 분할)

  • Kim Sung-Dong
    • Journal of KIISE:Software and Applications
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    • v.32 no.5
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    • pp.385-395
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    • 2005
  • Long sentence analysis has been a critical problem in machine translation because of high complexity. The methods of intra-sentence segmentation have been proposed to reduce parsing complexity. This paper presents the intra-sentence segmentation method based on maximum entropy probability model to increase the coverage and accuracy of the segmentation. We construct the rules for choosing candidate segmentation positions by a teaming method using the lexical context of the words tagged as segmentation position. We also generate the model that gives probability value to each candidate segmentation positions. The lexical contexts are extracted from the corpus tagged with segmentation positions and are incorporated into the probability model. We construct training data using the sentences from Wall Street Journal and experiment the intra-sentence segmentation on the sentences from four different domains. The experiments show about $88\%$ accuracy and about $98\%$ coverage of the segmentation. Also, the proposed method results in parsing efficiency improvement by 4.8 times in speed and 3.6 times in space.

Character Segmentation Using Side Profile Pattern (측면 윤곽 패턴을 이용한 접합 문자 분할법)

  • 정민철
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.4 no.3
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    • pp.248-251
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    • 2003
  • In this paper, a new segmentation method of machine printed character string with arbitrary length is proposed. Character recognition requires character segmentation as a previous step. However character segmentation itself requires a character recognition capability for less error segmentation. It is necessary to attack both these problem simultaneously. It is proposed that a new recognition-based segmentation method, which recognizes a character in touching characters with help of defined side-profiles. The match of ‘side-profiles of touching characters' with ‘side-profiles of prototypes' gives single character candidates in touching characters. It segments touching characters according to cutting costs.

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Automatic Phonetic Segmentation of Korean Speech Signal Using Phonetic-acoustic Transition Information (음소 음향학적 변화 정보를 이용한 한국어 음성신호의 자동 음소 분할)

  • 박창목;왕지남
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.8
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    • pp.24-30
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    • 2001
  • This article is concerned with automatic segmentation for Korean speech signals. All kinds of transition cases of phonetic units are classified into 3 types and different strategies for each type are applied. The type 1 is the discrimination of silence, voiced-speech and unvoiced-speech. The histogram analysis of each indicators which consists of wavelet coefficients and SVF (Spectral Variation Function) in wavelet coefficients are used for type 1 segmentation. The type 2 is the discrimination of adjacent vowels. The vowel transition cases can be characterized by spectrogram. Given phonetic transcription and transition pattern spectrogram, the speech signal, having consecutive vowels, are automatically segmented by the template matching. The type 3 is the discrimination of vowel and voiced-consonants. The smoothed short-time RMS energy of Wavelet low pass component and SVF in cepstral coefficients are adopted for type 3 segmentation. The experiment is performed for 342 words utterance set. The speech data are gathered from 6 speakers. The result shows the validity of the method.

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A Vertical Partitioning Algorithm based on Fuzzy Graph (퍼지 그래프 기반의 수직 분할 알고리즘)

  • Son, Jin-Hyun;Choi, Kyung-Hoon;Kim, Myoung-Ho
    • Journal of KIISE:Databases
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    • v.28 no.3
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    • pp.315-323
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    • 2001
  • The concept of vertical partitioning has been discussed so far in an objective of improving the performance of query execution and system throughput. It can be applied to the areas where the match between data and queries affects performance, which includes partitioning of individual files in centralized environments, data distribution in distributed databases, dividing data among different levels of memory hierarchies, and so on. In general, a vertical partitioning algorithm should support n-ary partitioning as well as a globally optimal solution for the generation of all meaningful fragments. Most previous methods, however, have some limitations to support both of them efficiently. Because the vertical partitioning problem basically includes the fuzziness property, the proper management is required for the fuzziness problem. In this paper we propose an efficient vertical $\alpha$-partitioning algorithm which is based on the fuzzy theory. The method can not only generate all meaningful fragments but also support n-ary partitioning without any complex mathematical computations.

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Character Segmentation with Segmentation Cost in Optical Character Recognition (문자 인식에서 분할 비용에 따른 문자 분할 연구)

  • Jung Minchul
    • Proceedings of the KAIS Fall Conference
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    • pp.179-181
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    • 2004
  • 인쇄체 문자 인식에서 접합 문자는 주요한 에러 발생의 원인이다. 본 논문에서는 접합 문자를 분할하기 위해 두 개의 분할 비용을 정의한다. 첫째, 절단 비용은 한 패턴을 분할하는 데 얼마나 많은 블랙픽셀이 분리되어야 하는가이다. 둘째, 접선 비용은 분할선이 얼마나 많은 블랙 픽셀과 화이트 픽셀사이를 지나가는가이다. 폰트 분류기는 접합 문자의 후보 문자를 제공한다. 후보 문자의 문자 폭은 접합 문자를 분리하기 위한 기준선을 제공하며, 그 기준선 부근의 픽셀들이 분할 가능 영역을 나타낸다. 절단 비용의 최소값과 접선 비용의 최대값이 되는 지점이 최종적으로 접합 문자를 분할하는 위치이다. 이렇게 정의된 절단 비용과 접선 비용을 가지고 접합 문자를 분할하면 보다 정확한 문자 분할을 하여 문자 인식에서 에러 발생을 줄일 수 있다.

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A Method for the Region Segmentation for Satellite Images using Region Split and Merge (영역 분할 및 합병 기법을 이용한 위성 영상 영역 분할 방법)

  • Chun, Byung-Tae;Jang, Dae-Geun
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.2
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    • pp.47-52
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    • 2007
  • Conventional pixel based region segmentation methods have problems of long processing time and incorrect region split on account of performing region split through comparison of neighboring pixels. In this paper, we propose the method which segments a large size of satellite image effectively using modified centroid linkage method. This method is a sort of region split and merge. The proposed method merges pixels and makes them as a new region through only two directional comparing the current positioning pixel with neighbor ones, if they are satisfied with given conditions. Therefore, this method has less comparing time than the cases of previous ones. The experimental result shows that the proposed method is very efficient because of having less processing time and more exact segmented regions than the previous ones.

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A Stable Multilevel Partitioning Algorithm for VLSI Circuit Designs Using Adaptive Connectivity Threshold (가변적인 연결도 임계치 설정에 의한 대규모 집적회로 설계에서의 안정적인 다단 분할 방법)

  • 임창경;정정화
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.35C no.10
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    • pp.69-77
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    • 1998
  • This paper presents a new efficient and stable multilevel partitioning algorithm for VLSI circuit design. The performance of multilevel partitioning algorithms that are proposed to enhance the performance of previous iterative-improvement partitioning algorithms for large scale circuits, depend on choice of construction methods for partition hierarchy. As the most of previous multilevel partitioning algorithms forces experimental constraints on the process of hierarchy construction, the stability of their performances goes down. The lack of stability causes the large variation of partition results during multiple runs. In this paper, we minimize the use of experimental constraints and propose a new method for constructing partition hierarchy. The proposed method clusters the cells with the connection status of the circuit. After constructing the partition hierarchy, a partition improvement algorithm, HYIP$^{[11]}$ using hybrid bucket structure, unclusters the hierachy to get partition results. The experimental results on ACM/SIGDA benchmark circuits show improvement up to 10-40% in minimum outsize over the previous algorithm $^{[3] [4] [5] [8] [10]}$. Also our technique outperforms ML$^{[10]}$ represented multilevel partition method by about 5% and 20% for minimum and average custsize, respectively. In addition, the results of our algorithm with 10 runs are better than ML algorithm with 100 runs.

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Block-based Color Image Segmentation Using HSV Color Space. (HSV 칼라를 이용한 블록단위 영상 분할)

  • 서동하;임재혁;원치선
    • Proceedings of the IEEK Conference
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    • pp.651-654
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    • 2000
  • 본 논문에서는 칼라 영역으로 확장된 블록단위 영상분할 알고리듬을 제안한다. 즉, 기존의 휘도 성분을 기반으로 한 블록단위 알고리듬을 HSV 칼라 성분을 기반으로 하는 칼라 영상분할로 확장한다. 기존의 수학적 형태학(mathematical morphology)에 기반한 영상분할기법이나 블록단위 영상분할 기법들이 밝기 정보만을 활용했던 것에 대해 제안된 블록단위 영상분할 기법은 밝기뿐만이 아니라 칼라 성분도 고려하여 영상분할의 정확도를 향상시켰다. 실험의 결과 휘도 성분만을 고려한 영상분할 결과 보다 칼라 성분을 사용한 영상분할의 결과가 더 정확함을 알 수 있었다.

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