• Title, Summary, Keyword: 영상 클러스트

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Study on the Film Industry Cluster through the Policy Comparison of Regional Film Industry - Focus on the Metropolitan, Busan, Jeonju Areas - (지역 영상산업 정책비교를 통한 영상산업 클러스트 연구 - 수도권, 부산, 전주를 중심으로 -)

  • Kim, Jin-Hae
    • The Journal of the Korea Contents Association
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    • v.8 no.9
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    • pp.115-123
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    • 2008
  • The purpose of this research is how to build the film industry cluster compare with the policies of metropolitan areas and local film industry. This research select four areas including Seoul and Kyunggi areas and Busan, Jeonju. And through the compare with the film industry infra & policies which results in as follows. This research suggest that film industry cluster devided into the two types. The one is the Film Industry Cluster Type and the other is Film Connected Tourism Business Cluster Type. Film Industry Cluster Type is devided into international competitive cities and domestic film industry cities. We suggest that Seoul, Kyunggi and Busan areas are designated to international competitive cities and Jeonju and Daejeon areas are designated to domestical cities. And the kwangwon, Chungcheng, Cheju Areas designated to Film Connected Tourism Business Cluster for location and open set business to improve the local development.

Performance Evaluation of Parallel BMA on Networked Cluster of Workstations (워크스테이션 클러스트 환경에서 병렬 BMA의 구현 및 성능 분석)

  • 김종렬;나현태;김정선;문영식
    • Proceedings of the Korean Information Science Society Conference
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    • pp.753-755
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    • 1999
  • 본 논문에서는 동영상에서 움직임 벡터를 찾는 방법 중의 하나인 BMA(Block Matching Algorithm)를 워크스테이션 클러스터(cluster of workstations) 환경하에서 구현하고 이에 대한 성능 분석 모델을 제시한다. 동영상에서 움직임 벡터를 찾는 BMA는 영상처리 및 컴퓨터 비전 분야에서 널리 사용되는 방법으로 병렬화를 통해 처리 속도를 단축시킬수 있는 알고리즘이다. 그러나 워크스테이션 클러스트 환경하에서는 데이터의 분할 및 각 노드간의 통신방법에 따라서 전체적인 성능에 많은 영향을 미친다. 따라서 본 논문에서는 최적의 데이터 분할 및 각 노드간의 통신을 최소화하는 병렬 BMA를 설계.구현한다. 또한 데이터의 분할 및 각 노드간의 통신을 고려한 성능 모델을 제시하여 프로세서의 증가 및 데이터의 분배에 따른 성능을 예측하고, 실험 결과를 통하여 제시한 모델의 타당성을 입증한다.

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Image Segmentation Based on the Fuzzy Clustering Algorithm using Average Intracluster Distance (평균내부거리를 적용한 퍼지 클러스터링 알고리즘에 의한 영상분할)

  • You, Hyu-Jai;Ahn, Kang-Sik;Cho, Seok-Je
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.9
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    • pp.3029-3036
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    • 2000
  • Image segmentation is one of the important processes in the image information extraction for computer vision systems. The fuzzy clustering methods have been extensively used in the image segmentation because it extracts feature information of the region. Most of fuzzy clustering methods have used the Fuzzy C-means(FCM) algorithm. This algorithm can be misclassified about the different size of cluster because the degree of membership depends on highly the distance between data and the centroids of the clusters. This paper proposes a fuzzy clustering algorithm using the Average Intracluster Distance that classifies data uniformly without regard to the size of data sets. The Average Intracluster Distance takes an average of the vector set belong to each cluster and increases in exact proportion to its size and density. The experimental results demonstrate that the proposed approach has the g

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A Design of AMCS(Agricultural Machine Control System) for the Automatic Control of Smart Farms (스마트 팜의 자동 제어를 위한 AMCS(Agricultural Machine Control System) 설계)

  • Jeong, Yina;Lee, Byungkwan;Ahn, Heuihak
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.12 no.3
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    • pp.201-210
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    • 2019
  • This paper proposes the AMCS(Agricultural Machine Control System that distinguishes farms using satellite photos or drone photos of farms and controls the self-driving and operation of farm drones and tractors. The AMCS consists of the LSM(Local Server Module) which separates farm boundaries from sensor data and video image of drones and tractors, reads remote control commands from the main server, and then delivers remote control commands within the management area through the link with drones and tractor sprinklers and the PSM that sets a path for drones and tractors to move from the farm to the farm and to handle work at low cost and high efficiency inside the farm. As a result of AMCS performance analysis proposed in this paper, the PSM showed a performance improvement of about 100% over Dijkstra algorithm when setting the path from external starting point to the farm and a higher working efficiency about 13% than the existing path when setting the path inside the farm. Therefore, the PSM can control tractors and drones more efficiently than conventional methods.