• Title/Summary/Keyword: content based retrieval

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Estimation of Soil Moisture Content from Backscattering Coefficients Using a Radar Scatterometer (레이더 산란계 후방산란계수를 이용한 토양수분함량 추정)

  • Kim, Yi-Hyun;Hong, Suk-Young;Lee, Jae-Eun
    • Korean Journal of Soil Science and Fertilizer
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    • v.45 no.2
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    • pp.127-134
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    • 2012
  • Microwave remote sensing can help monitor the land surface water cycle, crop growth and soil moisture. A ground-based polarimetric scatterometer has an advantage for continuous crop using multi-polarization and multi-frequencies and various incident angles have been used extensively in a frequency range expanding from L-band to Ka-band. In this study, we analyzed the relationships between L-, C- and X-band signatures and soil moisture content over the whole soybean growth period. Polarimetric backscatter data at L-, C- and X-bands were acquired every 10 minutes. L-band backscattering coefficients were higher than those observed using C- or X-band over the period. Backscattering coefficients for all frequencies and polarizations increased until Day Of Year (DOY) 271 and then decreased until harvesting stage (DOY 294). Time serious of soil moisture content was not a corresponding with backscattering over the whole growth stage, although it increased relatively until early August (R2, DOY 224). We conducted the relationship between the backscattering coefficients of each band and soil moisture content. Backscattering coefficients for all frequencies were not correlated with soil moisture content when considered over the entire stage ($r{\leq}0.50$). However, we found that L-band HH polarization was correlated with soil moisture content (r=0.90) when Leaf Area Index (LAI)<2. Retrieval equations were developed for estimating soil moisture content using L-band HH polarization. Relation between L-HH and soil moisture shows exponential pattern and highly related with soil moisture content ($R^2=0.92$). Results from this study show that backscattering coefficients of radar scatterometer appear effective to estimate soil moisture content.

Categorizing Web Image Search Results Using Emotional Concepts (감성 개념을 이용한 웹 이미지 검색 결과 분류)

  • Kim, Young-Rae;Kwon, Kyung-Su;Shin, Yun-Hee;Kim, Eun-Yi
    • 한국HCI학회:학술대회논문집
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    • 2009.02a
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    • pp.562-566
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    • 2009
  • In this paper, we present a novel system to categorize web image search results using emotional concepts and to browse the results more conveniently and easily. The proposed system can categorize search results into 8 emotional categories based on emotion vector, which obtained by color and pattern features. Here, we use Kobayashi’s emotional categories: {romantic, natural, casual, elegant, chic, classic, dandy and modern}. With search results for a given query, the proposed system can provide categorized images for each emotional category. With 1,000 Yahoo! search images, we compared the proposed method with Yahoo! image search engine in respect of satisfaction, efficiency, convenience and relevance with a user study. Our experimental results show the effectiveness of the proposed method.

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Movement Search in Video Stream Using Shape Sequence (동영상에서 모양 시퀀스를 이용한 동작 검색 방법)

  • Choi, Min-Seok
    • Journal of Korea Multimedia Society
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    • v.12 no.4
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    • pp.492-501
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    • 2009
  • Information on movement of objects in videos can be used as an important part in categorizing and separating the contents of a scene. This paper is proposing a shape-based movement-matching algorithm to effectively find the movement of an object in video streams. Information on object movement is extracted from the object boundaries from the input video frames becoming expressed in continuous 2D shape information while individual 2D shape information is converted into a lD shape feature using the shape descriptor. Object movement in video can be found as simply as searching for a word in a text without a separate movement segmentation process using the sequence of the shape descriptor listed according to order. The performance comparison results with the MPEG-7 shape variation descriptor showed that the proposed method can effectively express the movement information of the object and can be applied to movement search and analysis applications.

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A Study of CBIR(Content-based Image Retrieval) Computer-aided Diagnosis System of Breast Ultrasound Images using Similarity Measures of Distance (거리 기반 유사도 측정을 통한 유방 초음파 영상의 내용 기반 검색 컴퓨터 보조 진단 시스템에 관한 연구)

  • Kim, Min-jeong;Cho, Hyun-chong
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.8
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    • pp.1272-1277
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    • 2017
  • To assist radiologists for the characterization of breast masses, Computer-aided Diagnosis(CADx) system has been studied. The CADx system can improve the diagnostic accuracy of radiologists by providing objective information about breast masses. Morphological and texture features were extracted from the breast ultrasound images. Based on extracted features, the CADx system retrieves masses that are similar to a query mass from a reference library using a k-nearest neighbor (k-NN) approach. Eight similarity measures of distance, Euclidean, Chebyshev(Minkowski family), Canberra, Lorentzian($F_2$ family), Wave Hedges, Motyka(Intersection family), and Cosine, Dice(Inner Product family) are evaluated by ROC(Receiver Operating Characteristic) analysis. The Inner Product family measure used with the k-NN classifier provided slightly higher performance for classification of malignant and benign masses than those with the Minkowski, $F_2$, and Intersection family measures.

Classification of Man-Made and Natural Object Images in Color Images

  • Park, Chang-Min;Gu, Kyung-Mo;Kim, Sung-Young;Kim, Min-Hwan
    • Journal of Korea Multimedia Society
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    • v.7 no.12
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    • pp.1657-1664
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    • 2004
  • We propose a method that classifies images into two object types man-made and natural objects. A central object is extracted from each image by using central object extraction method[1] before classification. A central object in an images defined as a set of regions that lies around center of the image and has significant color distribution against its surrounding. We define three measures to classify the object images. The first measure is energy of edge direction histogram. The energy is calculated based on the direction of only non-circular edges. The second measure is an energy difference along directions in Gabor filter dictionary. Maximum and minimum energy along directions in Gabor filter dictionary are selected and the energy difference is computed as the ratio of the maximum to the minimum value. The last one is a shape of an object, which is also represented by Gabor filter dictionary. Gabor filter dictionary for the shape of an object differs from the one for the texture in an object in which the former is computed from a binarized object image. Each measure is combined by using majority rule tin which decisions are made by the majority. A test with 600 images shows a classification accuracy of 86%.

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QuLa: Queue and Latency-Aware Service Selection and Routing in Service-Centric Networking

  • Smet, Piet;Simoens, Pieter;Dhoedt, Bart
    • Journal of Communications and Networks
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    • v.17 no.3
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    • pp.306-320
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    • 2015
  • Due to an explosive growth in services running in different datacenters, there is need for service selection and routing to deliver user requests to the best service instance. In current solutions, it is generally the client that must first select a datacenter to forward the request to before an internal load-balancer of the selected datacenter can select the optimal instance. An optimal selection requires knowledge of both network and server characteristics, making clients less suitable to make this decision. Information-Centric Networking (ICN) research solved a similar selection problem for static data retrieval by integrating content delivery as a native network feature. We address the selection problem for services by extending the ICN-principles for services. In this paper we present Queue and Latency, a network-driven service selection algorithm which maps user demand to service instances, taking into account both network and server metrics. To reduce the size of service router forwarding tables, we present a statistical method to approximate an optimal load distribution with minimized router state required. Simulation results show that our statistical routing approach approximates the average system response time of source-based routing with minimized state in forwarding tables.

Multi-Dimensional Vector Approximation Tree with Dynamic Bit Allocation (동적 비트 할당을 통한 다차원 벡터 근사 트리)

  • 복경수;허정필;유재수
    • The Journal of the Korea Contents Association
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    • v.4 no.3
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    • pp.81-90
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    • 2004
  • Recently, It has been increased to use a multi-dimensional data in various applications with a rapid growth of the computing environment. In this paper, we propose the vector approximate tree for content-based retrieval of multi-dimensional data. The proposed index structure reduces the depth of tree by storing the many region information in a node because of representing region information using space partition based method and vector approximation method. Also it efficiently handles 'dimensionality curse' that causes a problem of multi-dimensional index structure by assigning the multi-dimensional data space to dynamic bit. And it provides the more correct regions by representing the child region information as the parent region information relatively. We show that our index structure outperforms the existing index structure by various experimental evaluations.

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Region-based H.263 Video Codec with Effective Rate Control Algorithm for Low VBR Video (개선된 특징차 비교 방법을 이용한 컷 검출 알고리즘에 관한 연구)

  • 최인호;이대영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.9B
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    • pp.1690-1696
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    • 1999
  • Video sequence should be hierachically classified for the content-based retrieval. Cut detection algorithm is an essential process to classify shots. It is generally difficult for cut detection algorithms to detect cut points since a current frame is compared with a previous one, because movement of camera or object made adrupt scene change. We reduce ratio of failed cut detection so that compare the difference between frames of predicted cut point and their neighbors. In this paper, first we get predicted cut point, then we judge that the predicted cut point is true point or not. And we extracted DC images in MPEG video sequence for comparison. As a result of experiments. We confirmed that the cut detection ratio of the proposed algorithm is higher than of any other algorithms.

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A Multi-Stage Approach to Secure Digital Image Search over Public Cloud using Speeded-Up Robust Features (SURF) Algorithm

  • AL-Omari, Ahmad H.;Otair, Mohammed A.;Alzwahreh, Bayan N.
    • International Journal of Computer Science & Network Security
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    • v.21 no.12
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    • pp.65-74
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    • 2021
  • Digital image processing and retrieving have increasingly become very popular on the Internet and getting more attention from various multimedia fields. That results in additional privacy requirements placed on efficient image matching techniques in various applications. Hence, several searching methods have been developed when confidential images are used in image matching between pairs of security agencies, most of these search methods either limited by its cost or precision. This study proposes a secure and efficient method that preserves image privacy and confidentially between two communicating parties. To retrieve an image, feature vector is extracted from the given query image, and then the similarities with the stored database images features vector are calculated to retrieve the matched images based on an indexing scheme and matching strategy. We used a secure content-based image retrieval features detector algorithm called Speeded-Up Robust Features (SURF) algorithm over public cloud to extract the features and the Honey Encryption algorithm. The purpose of using the encrypted images database is to provide an accurate searching through encrypted documents without needing decryption. Progress in this area helps protect the privacy of sensitive data stored on the cloud. The experimental results (conducted on a well-known image-set) show that the performance of the proposed methodology achieved a noticeable enhancement level in terms of precision, recall, F-Measure, and execution time.

Content Analysis of Articles on the Mobile Based Tourism Information (모바일 관광정보 연구논문에 관한 내용분석)

  • Ko, YoungKwan;Kim, Mincheol
    • Journal of Digital Convergence
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    • v.10 no.10
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    • pp.203-214
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    • 2012
  • As users of mobile devices such as smart phone are rapidly growing owing to the development of information technology, interest for information retrieval and a variety of services using mobile devices is gradually increasing. Users want to get the tourist information service through the use of mobile devices and accordingly, Korea local governments are trying to provide a variety of services on the mobile tourist information via smart phone. As more interest and requirements on mobile tourist information service, researches on types and preferences of mobile tourist information, measurement of the quality of service, the user's satisfaction and re-use is currently being done. However, meanwhile, the research on the content analysis classified and investigated a wide variety of numerical rating scale such as research topics of research papers, research methodology is wholly lacking. Thus, in terms of the research need on a systematic study of the domestic mobile tourist information, this study presented the research tendencies and implications of yearly research trends, research subjects, statistical analysis techniques, research methods, research models and theories related to the mobile tourist information focusing on journals listed on the National Research Foundation of Korea.