• Title/Summary/Keyword: Target extraction

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Web Information Extraction using HTML Tag Pattern (HTML 태그페턴을 이용한 웹정보추출시스템)

  • Park, Byung-Kwon
    • Proceedings of the Korea Association of Information Systems Conference
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    • 2005.05a
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    • pp.79-92
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    • 2005
  • To query the vast amount of web pages which are available i]l the Internet, it is necessary to extract the encoded information in the web pages for converting it into structured data (e.g. relational data for SQL) or semistructured data (e.g. XML data for XQuery), In this paper, we propose a new web information extraction system, PIES, to convert web information into XML documents. PIES is based on a user-specified target schema and HTML tag pattern descriptions. The web information is extracted by the pattern descriptions and validated by the target schema. We designed a new language to describe extraction rules, and a new regular expression to describe HTML tag patterns. We implemented PIES and applied it to the US patent web site to evaluate its correctness. It successfully extracted more than thousands of US patent data and converted them into XML documents.

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Opto-Digital Implementation of Convergence-Controlled Stereo Target Tracking System (주시각이 제어된 스테레오 물체추적 시스템의 광-디지털적 구현)

  • 고정환;이재수;김은수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.4B
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    • pp.353-364
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    • 2002
  • In this paper, a new onto-digital stereo object-tracking system using hierarchical digital algorithms and optical BPEJTC is proposed. This proposed system can adaptively track a moving target by controlling the convergence of stereo camera. firstly, the target is detected through the background matching of the sequential input images by using optical BPEJTC and then the target area is segmented by using the target projection mask which is composed by hierarchical digital processing of image subtraction, logical operation and morphological filtering. Secondly, the location's coordinate of the moving target object for each of the sequential input frames can be extracted through carrying out optical BPEJTC between the reference image of the target region mask and the stereo input image. Finally, the convergence and pan/tilt of stereo camera can be sequentially controlled by using these target coordinate values and the target can be kept in tracking. Also, a possibility of real-time implementation of the adaptive stereo object tracking system is suggested through optically implementing the proposed target extraction and convergence control algorithms.

A Study on Vehicle Target Classification Method Using Both Shape and Local Features with Segmentation Reliability (표적분할 신뢰도 값 기반의 형태특징과 지역특징을 이용한 차량표적 분류기법 연구)

  • Yang, DongWon;Lee, Yonghun;Kwak, Dongmin
    • Journal of the Korea Institute of Military Science and Technology
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    • v.20 no.1
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    • pp.40-47
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    • 2017
  • To classify the vehicle targets automatically using thermal images, there are usually two main categories of feature extraction method, local and shape feature extraction methods. Since thermal images have less texture information than color images, the shape feature extraction method is useful when the segmentation results are correct. However, if there are some errors in target segmentation, the shape feature may contain some errors, then the classification accuracy can be decreased. To overcome these problems, in this paper, we propose the segmentation reliability estimation method for target classification. The segmentation reliability can be estimated by using the difference information of average intensities and edge energies between the target and the background area. The estimated segmentation reliability is applied in the decision level fusion method of classification results using both shape and local features. Experiment results using the thermal images of the vehicle targets (main battle tank, armored personnel carrier, military truck, and an estate car) show that the proposed classification method and the segmentation reliability estimation method have a good performance in classification accuracy.

FLIR and CCD Image Fusion Algorithm Based on Adaptive Weight for Target Extraction (표적 추출을 위한 적응적 가중치 기반 FLIR 및 CCD 센서 영상 융합 알고리즘)

  • Gu, Eun-Hye;Lee, Eun-Young;Kim, Se-Yun;Cho, Woon-Ho;Kim, Hee-Soo;Park, Kil-Houm
    • Journal of Korea Multimedia Society
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    • v.15 no.3
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    • pp.291-298
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    • 2012
  • In automatic target recognition(ATR) systems, target extraction techniques are very important because ATR performance depends on segmentation result. So, this paper proposes a multi-sensor image fusion method based on adaptive weights. To incorporate the FLIR image and CCD image, we used information such as the bi-modality, distance and texture. A weight of the FLIR image is derived from the bi-modality and distance measure. For the weight of CCD image, the information that the target's texture is more uniform than the background region is used. The proposed algorithm is applied to many images and its performance is compared with the segmentation result using the single image. Experimental results show that the proposed method has the accurate extraction performance.

Moving Target Tracking and Recognition for Location Based Surveillance Service (위치기반 감시 서비스를 위한 이동 객체 추적 및 인식)

  • Kim, Hyun;Park, Chan-Ho;Woo, Jong-Woo;Doo, Seok-Bae
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.1211-1212
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    • 2008
  • In this paper, we propose image process modeling as a part of location based surveillance system for unauthorized target recognition and tracking in harbor, airport, military zone. For this, we compress and store background image in lower resolution and perform object extraction and motion tracking by using sobel edge detection and difference picture method between real images and a background image. In addition to, we use Independent Component Analysis Neural Network for moving target recognition. Experiments are performed for object extraction and tracking of moving targets on road by using static camera in 20m height building and it shows the robust results.

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Development of Intelligent Surveillance System Using Stationary Camera for Multi-Target-Based Object Tracking (다중영역기반의 객체추적을 위한 고정형 카메라를 이용한 지능형 감시 시스템 개발)

  • Im, Jae-Hyun;Kim, Tae-Kyung;Choi, Kwang-Yong;Han, In-Kyo;Paik, Joon-Ki
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.789-790
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    • 2008
  • In this paper, we introduce the multi-target-based auto surveillance algorithm. Multi-target-based surveillance system detects intrusion objects in the specified areas. The proposed algorithm can divide into two parts: i) background generation, ii) object extraction. In this paper, one of the optical flow equation methods for estimation of gradient method used to generate the background [2]. In addition, the objects and back- ground video images that are continually entering the differential extraction.

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A New Algorithm for the Extraction of Target-Like Objects Using a Double Gate (이중 게이트를 사용한 새로운 유사 목표물 추출 기법)

  • 한기준;김영균
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.19 no.4
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    • pp.21-25
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    • 1982
  • This paper describes a new algorithm for the extraction of target-like objects. In order to extract target-like objects, a given image is transformed into two-valued image by thresholding, and then a double gate is applied to the two-valued image. With the synthetic-image data, we have shown the good performance of the new algorithm.

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Extraction of location of 3-D object from CIIR method based on blur effect of reconstructed POI

  • Park, Seok-Chan;Kim, Seung-Cheol;Kim, Eun-Soo
    • 한국정보디스플레이학회:학술대회논문집
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    • 2009.10a
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    • pp.1363-1366
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    • 2009
  • A new recognition method is used to find the three-dimensional target object on integral imaging. For finding the location of a target image, amount of reconstructed reference image is needed. This method is giving accurate information of target image by correlated among reconstructed target images and reference images.

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Feature Extraction for Robot Map Using Neural Network

  • Kim, Chang-Hyun;Oh, Chang-Mok;Lee, Ju-Jang
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.37.4-37
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    • 2002
  • $\textbullet$ Feature extraction method for robot application $\textbullet$ Using ultrasonic sensor arrays $\textbullet$ Differentiate the target as plane, corner and edge $\textbullet$ Neural network approach

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Development of a low energy ion irradiation system for erosion test of first mirror in fusion devices

  • Kihyun Lee;YoungHwa An;Bongki Jung;Boseong Kim;Yoo kwan Kim
    • Nuclear Engineering and Technology
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    • v.56 no.1
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    • pp.70-77
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    • 2024
  • A low energy ion irradiation system based on the deuterium arc ion source with a high perveance of 1 µP for a single extraction aperture has been successfully developed for the investigation of ion irradiation on plasma-facing components including the first mirror of plasma optical diagnostics system. Under the optimum operating condition for mirror testing, the ion source has a beam energy of 200 eV and a current density of 3.7 mA/cm2. The ion source comprises a magnetic cusp-type plasma source, an extraction system, a target system with a Faraday cup, and a power supply control system to ensure stable long time operation. Operation parameters of plasma source such as pressure, filament current, and arc power with D2 discharge gas were optimized for beam extraction by measuring plasma parameters with a Langmuir probe. The diode electrode extraction system was designed by IGUN simulation to optimize for 1 µP perveance. It was successfully demonstrated that the ion beam current of ~4 mA can be extracted through the 10 mm aperture from the developed ion source. The target system with the Faraday cup is also developed to measure the beam current. With the assistance of the power control system, ion beams are extracted while maintaining a consistent arc power for more than 10 min of continuous operation.