• Title/Summary/Keyword: FLIR

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Target extraction in FLIR image using Bi-modality of local characteristic and Chamfer distance (국부적 특성의 Bi-modality와 Chamfer 거리를 이용한 FLIR 영상의 표적 추출)

  • Lee, Hee-Yul;Kim, Se-Yun;Kim, Jong-Hwan;Kwak, Dong-Min;Choi, Byung-Jae;Joo, Young-Bok;Park, Kil-Houm
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.3
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    • pp.304-310
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    • 2009
  • In this paper, target extraction method in FLIR(forward-looking infrared) images based on fuzzy thresholding which used bi-modality and adjacency to determine membership value is proposed. The bi-modality represents how a pixel is classified into a part of target using distribution of pixel values in a local region, and The adjacency is a measure to represent how each pixel is far from the target region. First, membership value is calculated using above two measures, and then fuzzy thresholding is performed to extract the target. To evaluate performance of proposed target extraction method, we compare other segmentation methods using various FLIR tank image. Experimental results show that the proposed algorithm is a good segmentation performance.

Development of a Geo-Pointing System of Helicopter-Mounted FLIR (헬기 장착 전방관측적외선장비 좌표지향시스템 개발)

  • Kim, Sung-Su;Shin, Yong-San;Kim, Sung-Soo;Kwon, Kang-Hun
    • Journal of the Korea Institute of Military Science and Technology
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    • v.12 no.6
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    • pp.750-759
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    • 2009
  • FLIR(Forward Looking Infrared) geo-pointing is a function that helps pilots to see a target within the field of view under all coordinates and attitudes of helicopter. Geo-pointing controls FLIR LOS(line of sight) toward known target coordinates by using azimuth and elevation angles calculated from several information such as helicopter coordinates and attitudes, a FLIR position from a GPS antenna, and target coordinates. Geo-pointing performance has been tested and evaluated on the ground to save flight test costs and ensure flight safety. In this paper, design and implementation of a geo-pointing system is described with the results of performance test conducted on the ground test system.

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.

Small Target Detection Method under Complex FLIR Imagery (복잡한 FLIR 영상에서의 소형 표적 탐지 기법)

  • Lee, Seung-Ik;Kim, Ju-Young;Kim, Ki-Hong;Koo, Bon-Ho
    • Journal of Korea Multimedia Society
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    • v.10 no.4
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    • pp.432-440
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    • 2007
  • In this paper, we propose a small target detection algorithm for FLIR image with complex background. First, we compute the motion information of target from the difference between the current frame and the created background image. However, the slow speed of target cause that it has the very low gray level value in the difference image. To improve the gray level value, we perform the local gamma correction for difference image. So, the detection index is computed by using statistical characteristics in the improved image and then we chose the lowest detection index a true target. Experimental results show that the proposed method has significantly the good detection performance.

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Target extraction using divergent-direction-emphasis symmetry transform (발산 방향성 강조 대칭변환을 이용한 표적 검출)

  • Jun, Jun-Hyung;Lee, Hee-Yul;Choi, Byung-Jae;Park, Kil-Houm
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.5
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    • pp.665-671
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    • 2010
  • This paper propose the DDEGST(divergent-direction-emphasis generalized symmetry transform) which emphasis the symmetry of divergent intensity orientation for effective target extraction in FLIR(forward looking infra-red) images. In the proposed method, we use the exponential function instead of cosine function as a phase weight function in the generalized symmetry transform for effective target extraction in FLIR images which contain a target with higher intensity than a background intensity. To evaluate the performance of the proposed method, we compare the proposed mehtod with conventional GST method in experiments. We prove that the proposed method have better performance in IR images.

A Case Study on the Fracture of Steering Apparatus for Aircraft (항공기 조향장치 파손원인 사례연구)

  • Park, Sung-Ji
    • Journal of the Korean Society of Safety
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    • v.28 no.3
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    • pp.29-32
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    • 2013
  • An aircraft made an emergency landing through the loss of capability controlling steering. A torsion link which is a part of steering apparatus has been adrift from the steering system and the bolt connected to the steering link has fractured. At the same time, the FLIR(Forward Looking Infrared Radar) mounted in front of the steering link has been also damaged. In the early of this investigation, we considered the failure of the FLIR had occurred first, that FLIR hit the steering link and finally the bolt fractured. The fractured section of the bolt has shown a beach mark and a dimple mark as well. The outside of the bolt has shown a large deformation by a heavy load. As a result, we have found out what the cause of the heavy load and the fractures for bolt, link and FLIR have occurred in what order.

Object Recognition by Invariant Feature Extraction in FLIR (적외선 영상에서의 불변 특징 정보를 이용한 목표물 인식)

  • 권재환;이광연;김성대
    • Proceedings of the IEEK Conference
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    • 2000.11d
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    • pp.65-68
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    • 2000
  • This paper describes an approach for extracting invariant features using a view-based representation and recognizing an object with a high speed search method in FLIR. In this paper, we use a reformulated eigenspace technique based on robust estimation for extracting features which are robust for outlier such as noise and clutter. After extracting feature, we recognize an object using a partial distance search method for calculating Euclidean distance. The experimental results show that the proposed method achieves the improvement of recognition rate compared with standard PCA.

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Development of image tracking technic to moving target (이동중인 표적에 대한 영상추적기법의 개발)

  • 양승윤;이종헌;이만형
    • 제어로봇시스템학회:학술대회논문집
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    • 1988.10a
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    • pp.183-186
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    • 1988
  • The problem addressed in this paper is the accurate tracting of a dynamic target using outputs from a forward - looking infrared(FLIR) sensor as measurements. The important variations are 1) the spread of the target intensity pattern in the FLIR image plane, 2) target motion characteristics, and 3) the rms value and both spartial and temporal correlation of the back - ground noise. Based on this insights. design modifications and on - line adaptation copabilities are incorporated to enable this type of filter track highly maneuverable targets such as air-to-air missiles, with spatially distributed and changing image intensity profiles, against, background clutter.

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Object Detection in a Still FLIR Image using Intensity Ranking Feature (밝기순위 특징을 이용한 적외선 정지영상 내 물체검출기법)

  • Park Jae-Hee;Choi Hak-Hun;Kim Seong-Dae
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.2 s.302
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    • pp.37-48
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    • 2005
  • In this paper, a new object detection method for FLIR images is proposed. The proposed method consists of intensity ranking feature and a classification algerian using the feature. The intensity ranking feature is a representation of an image, from which intensity distribution is regularized. Each object candidate region is classified as object or non-object by the proposed classification algorithm which is based on the intensity ranking similarity between the candidate and object training images. Using the proposed algorithm pixel-wise detection results can be obtained without any additional candidate selection algorithm. In experimental results, it is shown that the proposed ranking feature is appropriate for object detection in a FLIR image and some vehicle detection results in the situation of existing noise, scale variation, and rotation of the objects are presented.