• 제목/요약/키워드: Centroid Extraction

검색결과 41건 처리시간 0.026초

이동경계의 무게중심에 의한 실시간 자동목표 추적 (Real-Time Automatic Target Tracking Using a Centroid of Moving Edges)

  • 배정효;김남철
    • 한국통신학회:학술대회논문집
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    • 한국통신학회 1987년도 춘계학술발표회 논문집
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    • pp.42-45
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    • 1987
  • In this paper a target tracking algorithm of the centroid extraction from moving edges is proposed, It aims to avoid the difficulty of imahe segmentation in case of the centroid extraction from one frame. The performance of the proposed algorithmfor noisy and occluded images is discussed Finally it is also applied to a real time target tracker.

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상표 영상 검색 시스템 (Trademark Image Retrieval System)

  • 신성윤;백성은;표성배;이양원
    • 한국컴퓨터정보학회지
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    • 제15권1호
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    • pp.185-190
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    • 2007
  • An image retrieval system is a piece of software that searches identical or similar images based on various image-specific features. This paper proposes a trademark image retrieval system that uses image colors and forms. In the proposed system, input images are segmented into several other regions, and color distribution histograms for different regions are extracted for use as color information. The proposed system uses form information through the preprocessing process such as boundary surface extraction, centroid extraction, angular sampling and, and through calculating the sums of the distances between the centroid and the boundary surfaces, standard deviations, and the ratios between long and short axes. Like this, the color and form information extracted is used to perform retrieval through measuring similarity.

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컬러와 형태에 기반을 둔 상표 영상 검색 시스템 (The Brand Image Retrieval System Based on Color and Shape)

  • 신성윤;표성배
    • 한국컴퓨터정보학회논문지
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    • 제11권3호
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    • pp.167-172
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    • 2006
  • 영상 검색 시스템이란 영상이 갖는 다양한 특징을 바탕으로 똑같거나 유사한 영상을 검색하여 제공하는 시스템이다. 본 논문에서는 영상의 컬러와 형태를 기반으로 한 상표 영상 검색 시스템을 제시한다. 영상을 영역별로 분할하고 영역별 컬러 분포 히스토그램을 추출하여 컬러 정보로 이용한다. 경계면 추출, 무게 중심 추출, angular 샘플링 등의 전처리 과정과 무게 중심으로부터 경계면 까지 거리의 합, 표준 편차, 장/단축 비율을 계산하여 형태정보로 이용한다. 이렇게 추출된 컬러와 형태 정보를 이용하여 유사성 측정을 통한 검색을 수행한다.

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Ocean Surface Current Retrieval Using Doppler Centroid of ERS-1 Raw SAR Data

  • Kim Ji-Eun;Kim Duk-jin;Moon Wooil M.
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.590-593
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    • 2004
  • Extraction of ocean surface current velocity offers important physical oceanographic parameters especially on understanding ocean environment. Although Remote Sensing techniques were highly developed, the investigation of ocean surface current using Synthetic Aperture Radar (SAR) is not an easy task. This paper presents the results of ocean surface current observation using Doppler Centroid of ERS-1 SAR data obtained off the coast of Korea peninsula. We employed the concept, in which Doppler frequency shift and the ocean surface current are closely related, to evaluate ocean surface current. Moving targets cause Doppler frequency shift of the back scattered radar waves of SAR, thus the line-of-sight velocity component of the scatters can be evaluated. The Doppler frequency shift can be measured by estimating the difference between Doppler Centroid of raw SAR data and reference Doppler Centroid. Theoretically, the Doppler Centroid is zero; however, squinted antenna which is affected by several physical factors causes Doppler Centroid to be nonzero. The reference Doppler Centroid can be obtained from measurements of sensor trajectory, attitude and Earth model. The estimated Doppler Centroid was compensated by considering the accurate attitude estimation of ERS-1 SAR. We could verify the correspondence between the estimated ocean surface current and observed in-situ data in the error bound.

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An Efficient Extraction of Pulmonary Parenchyma in CT Images using Connected Component Labeling

  • Thapaliya, Kiran;Park, Il-Cheol;Kwon, Goo-Rak
    • Journal of information and communication convergence engineering
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    • 제9권6호
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    • pp.661-665
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    • 2011
  • This paper presents the method for the extraction of the lungs part from the other parts for the diagnostic of the lungs part. The proposed method is based on the calculation of the connected component and the centroid of the image. Connected Component labeling is used to label the each objects in the binarized image. After the labeling is done, centroid value is calculated for each object. The filing operation is applied which helps to extract the lungs part from the image retaining all the parts of the original lungs image. The whole process is explained in the following steps and experimental results shows it's significant.

Centroid 위치벡터를 이용한 영상 검색 기법 (A Centroid-based Image Retrieval Scheme Using Centroid Situation Vector)

  • 방상배;남재열;최재각
    • 방송공학회논문지
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    • 제7권2호
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    • pp.126-135
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    • 2002
  • 영상은 색상, 형태, 위치, 질감 같은 다양한 특성을 갖고 있기 때문에 하나의 특성만을 이용하여 일괄적으로 영상을 검색할 경우, 만족할 만한 검색효율을 얻기가 어렵다. 특히, 대용량의 영상 데이터베이스일수록 그 같은 현상은 빈번하게 일어나기 때문에 기존의 내용 기반 영상 검색 시스템들은 대부분 하나 이상의 특성을 이용하여 검색효율 향상을 죄하고 있다. 본 논문에서는 Centroid 위치벡터를 이용하여 영상 내의 색상 정보뿐만 아니라, 특정 색상에 대한 위치정보를 고려하는 기법을 제안한다. 질의영상의 한 색상에 대해 Centroid 위치벡터를 추출하고 비교영상의 같은 색상의 Centroid 위치벡터와의 거리를 비교하여 그 거리가 짧을수록 각 색상의 위치 유사도를 높게 책정하는 방식을 제안한다. 제안된 검색 기법은 기존의 색상 분포만을 이용하는 검색 기법에 비해, 원근 처리된 영상에 강인하고, 회전되거나 뒤집힌 영상의 변별력이 향상되었다. 또한, 제안된 방식은 색상정보와 위치정보의 추출을 이원화시키지 않고 동시에 추출함으로써 계산량을 줄이고, 효율적인 색인 파일을 생성하여 검색속도를 향상시켰다.

효율적인 상표 영상 검색 시스템 (System of Efficient Trademark Image Retrieval)

  • 신성윤;백정욱;이양원
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2010년도 춘계학술대회
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    • pp.160-161
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    • 2010
  • 본 논문에서는 컬러 정보와 형태 정보를 이용한 상표 영상 검색 시스템을 제안하였다. 컬러 정보는 영역을 분할하여 영역별 컬러 분포 히스토그램 특성에 근거한 컬러 정보를 이용하였고, 형태 정보는 경계면 추출, 무게 중심 추출, angular 샘플링 등의 전처리 과정과 무게 중심으로부터 경계면까지 거리의 합, 표준 편차, 장/단축 비율을 계산을 이용하였다. 특히, 무게중심을 이용한 angular 샘플링을 이용하여 특징을 추출하고 처리 시간을 줄일 수 있었다. 사용자는 컬러와 형태 정보에 의한 검색을 수행하고, 또한 가중치를 부여함으로써 두 방법을 혼합하여 사용할 수 있다.

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Morphological Feature Extraction of Microorganisms Using Image Processing

  • Kim Hak-Kyeong;Jeong Nam-Su;Kim Sang-Bong;Lee Myung-Suk
    • Fisheries and Aquatic Sciences
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    • 제4권1호
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    • pp.1-9
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    • 2001
  • This paper describes a procedure extracting feature vector of a target cell more precisely in the case of identifying specified cell. The classification of object type is based on feature vector such as area, complexity, centroid, rotation angle, effective diameter, perimeter, width and height of the object So, the feature vector plays very important role in classifying objects. Because the feature vectors is affected by noises and holes, it is necessary to remove noises contaminated in original image to get feature vector extraction exactly. In this paper, we propose the following method to do to get feature vector extraction exactly. First, by Otsu's optimal threshold selection method and morphological filters such as cleaning, filling and opening filters, we separate objects from background an get rid of isolated particles. After the labeling step by 4-adjacent neighborhood, the labeled image is filtered by the area filter. From this area-filtered image, feature vector such as area, complexity, centroid, rotation angle, effective diameter, the perimeter based on chain code and the width and height based on rotation matrix are extracted. To prove the effectiveness, the proposed method is applied for yeast Zygosaccharomyces rouxn. It is also shown that the experimental results from the proposed method is more efficient in measuring feature vectors than from only Otsu's optimal threshold detection method.

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Arabic Text Clustering Methods and Suggested Solutions for Theme-Based Quran Clustering: Analysis of Literature

  • Bsoul, Qusay;Abdul Salam, Rosalina;Atwan, Jaffar;Jawarneh, Malik
    • Journal of Information Science Theory and Practice
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    • 제9권4호
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    • pp.15-34
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    • 2021
  • Text clustering is one of the most commonly used methods for detecting themes or types of documents. Text clustering is used in many fields, but its effectiveness is still not sufficient to be used for the understanding of Arabic text, especially with respect to terms extraction, unsupervised feature selection, and clustering algorithms. In most cases, terms extraction focuses on nouns. Clustering simplifies the understanding of an Arabic text like the text of the Quran; it is important not only for Muslims but for all people who want to know more about Islam. This paper discusses the complexity and limitations of Arabic text clustering in the Quran based on their themes. Unsupervised feature selection does not consider the relationships between the selected features. One weakness of clustering algorithms is that the selection of the optimal initial centroid still depends on chances and manual settings. Consequently, this paper reviews literature about the three major stages of Arabic clustering: terms extraction, unsupervised feature selection, and clustering. Six experiments were conducted to demonstrate previously un-discussed problems related to the metrics used for feature selection and clustering. Suggestions to improve clustering of the Quran based on themes are presented and discussed.

SAFT Based Imaging and Centroid Technique for Classification of UT Signals from the Steam Generator of a Nuclear Power Plant

  • Kim, Dae-Won
    • 비파괴검사학회지
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    • 제28권3호
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    • pp.263-272
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    • 2008
  • Many technical methods are used for nondestructive testing field for solid materials. Among those, ultrasonic inspection methods are widely used and one of the popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature space. This paper describes an approach which uses LMS method to determine the coordinates of the ultrasonic probe followed by the use of SAFT with centroid technique to estimate the location of the ultrasonic reflector. The method is employed for classifying UT-NDE signals from the steam generator tubes in a nuclear power plant. The classification results are presented for the ultrasonic signals from cracks and deposits within steam generator tubes.