• Title/Summary/Keyword: Automatic Information Extraction

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A Seamline Extraction Technique Considering the Characteristic of NDVI for High Resolution Satellite Image Mosaics (고해상도 위성영상 모자이크를 위한 NDVI 특성을 이용한 접합선 추출 기법)

  • Kim, Jiyoung;Chae, Taebyeong;Byun, Younggi
    • Korean Journal of Remote Sensing
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    • v.31 no.5
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    • pp.395-408
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    • 2015
  • High-resolution satellite image mosaics are becoming increasingly important in the field of remote sensing image analysis as an essential image processing to create a large image constructed from several smaller images. In this paper, we present an automatic seamline extraction technique and the procedure to generate a mosaic image by this technique. For more effective seamline extraction in the overlap region of adjacent images, an NDVI-based seamline extraction technique is developed, which takes advantage of the computational time and memory. The Normalized Difference Vegetation Index(NDVI) is an index of plant "greeness" or photosynthetic activity that is employed to extract the initial seamline. The NDVI can divide into manmade region and natural region. The cost image is obtained by the canny edge detector and the buffering technique is used to extract the ranging cost image. The seamline is extracted by applying the Dijkstra algorithm to a cost image generated through the labeling process of the extracted edge information. Histogram matching is also conducted to alleviate radiometric distortion between adjacent images acquired at different time. In the experimental results using the KOMPSAT-2/3 satellite imagery, it is confirmed that the proposed method greatly reduces the visual discontinuity caused by geometric difference of adjacent images and the computation time.

Study on improving the accuracy of automatic extraction from spatial information and land cover map (공간영상정보와 토지피복분류를 통한 피해지역 자동추출 정확도 향상에 관한 연구)

  • Seo, Jung-Taek;Kim, Kye-Hyun;Kim, Tae-Hoon
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2010.09a
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    • pp.72-76
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    • 2010
  • 최근 들어 고해상도 항공영상을 활용한 공간정보의 구축 및 활용 사례가 증가하고 있으며, 기 구축된 공간정보의 정확도 향상을 위한 추가적인 노력이 필요시 되고 있는 실정이다. 이에 본 연구에서는 기존의 피해 전 후 항공영상을 이용한 피해지역 자동추출에 있어 결과물의 정확도 향상을 위하여 토지피복도와의 중첩을 통한 피해항목의 선택적 추출과 자동 추출된 결과물의 오차 제거가 가능하도록 하였다. 연구 대상지역은 2008년 7월 말 국지성 집중호우로 인하여 큰 피해를 입은 경상북도 봉화군 춘양면 일대를 선정하였으며, 집중호우에 상당히 취약하고 당시 사유시설 중 피해액이 가장 컸던 농경지에 대해 본 연구를 시범 적용하였다. 결과적으로 토지피복분류를 통해 피해 전 후 영상의 해상도 차이와 시계열적인 차이로 인해 발생하는 자동추출 결과물의 잡음 제거가 가능하였으며, 항공영상정보와 달리 육안으로 피해 항목의 선별이 어려운 자동추출 결과물에서 피해항목의 선별이 가능하였다. 이는 나아가 피해지역의 피해액 산출에 있어 보다 정확한 계산이 가능하게 하며, 추후 국가적 피해조사 사업에 있어 신뢰성 높은 피해정보 생산에 큰 기여를 할 것으로 사료된다.

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Melanoma Classification Algorithm using Gray-level Conversion Matrix Feature and Support Vector Machine (회색도 변환 행렬 특징과 SVM을 이용한 흑색종 분류 알고리즘)

  • Koo, Jung Mo;Na, Sung Dae;Cho, Jin-Ho;Kim, Myoung Nam
    • Journal of Korea Multimedia Society
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    • v.21 no.2
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    • pp.130-137
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    • 2018
  • Recently, human life is getting longer due to change of living environment and development of medical technology, and silver medical technology has been in the limelight. Geriatric skin disease is difficult to detect early, and when it is missed, it becomes a malignant disease and is difficult to treatment. Melanoma is one of the most common diseases of geriatric skin disease and initially has a similar modality with the nevus. In order to overcome this problem, we attempted to perform a feature analysis in order to attempt automatic detection of melanoma-like lesions. In this paper, one is first order analysis using information of pixels in radiomic feature. The other is a gray-level co-occurrence matrix and a gray level run length matrix, which are feature extraction methods for converting image information into a matrix. The features were extracted through these analyses. And classification is implemented by SVM.

Moving Object Tracking Using Active Contour Model (동적 윤곽 모델을 이용한 이동 물체 추적)

  • Han, Kyu-Bum;Baek, Yoon-Su
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.27 no.5
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    • pp.697-704
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    • 2003
  • In this paper, the visual tracking system for arbitrary shaped moving object is proposed. The established tracking system can be divided into model based method that needs previous model for target object and image based method that uses image feature. In the model based method, the reliable tracking is possible, but simplification of the shape is necessary and the application is restricted to definite target mod el. On the other hand, in the image based method, the process speed can be increased, but the shape information is lost and the tracking system is sensitive to image noise. The proposed tracking system is composed of the extraction process that recognizes the existence of moving object and tracking process that extracts dynamic characteristics and shape information of the target objects. Specially, active contour model is used to effectively track the object that is undergoing shape change. In initializatio n process of the contour model, the semi-automatic operation can be avoided and the convergence speed of the contour can be increased by the proposed effective initialization method. Also, for the efficient solution of the correspondence problem in multiple objects tracking, the variation function that uses the variation of position structure in image frame and snake energy level is proposed. In order to verify the validity and effectiveness of the proposed tracking system, real time tracking experiment for multiple moving objects is implemented.

An Automatic Region-of-Interest Extraction based on Wavelet on Low DOF Image (피사계 심도가 낯은 이미지에서 웨이블릿 기반의 자동 관심 영역 추출)

  • Park, Sun-Hwa;Kang, Ki-Jun;Seo, Yeong-Geon;Lee, Bu-Kweon
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2009.01a
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    • pp.215-218
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    • 2009
  • 본 논문에서는 웨이블릿 변환 된 고주파 서브밴드들의 에지 정보를 이용하여 관심 객체 영역을 고속으로 자동 검출해주는 새로운 알고리즘을 제안하였다. 제안된 방법에서는 에지정보를 이용하여 블록단위의 4-방향 객체 윤곽 탐색 알고리즘(4-DOBS)을 수행하여 관심객체를 검출한다. 전체 이미지는 $64{\times}64$ 또는 $32{\times}32$ 크기의 코드 블록으로 먼저 나누어지고, 각 코드 블록 내에 에지들이 있는지 없는지에 따라 관심 코드블록 또는 배경이 된다. 4-방향은 바깥쪽에서 이미지의 중앙으로 탐색하여 접근하며, 피사계 심도가 낮은 이미지는 중앙으로 갈수록 에지가 발견된다는 특징을 이용한다. 기존 방법들의 문제점 이였던 복잡한 필터링 과정과 영역병합 문제로 인한 높은 계산도를 상당히 개선시킬 수 있었다. 또한 블록 단위의 처리로 인하여 실시간 처리를 요하는 응용에서도 적용 가능 하였다.

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Proposal of Feature Classification System for Land Change Detection (국토변화탐지를 위한 지형분류체계 개선안)

  • Park, Jun-Ku;Noh, Myoung-Jong;Cho, Woo-Sug;Bang, Ki-In
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.2
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    • pp.9-17
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    • 2011
  • For the exact status of the land such as land cover classification and land use classification, feature classification system has been utilized in several organizations and agencies. However, those classification systems are limited to detection of land change and it's also not suited for the extraction of land changed. In this study, we would proposed a standard feature classification system which presents both in natural and artificial change of land effectively. Based on comparison and analysis of domestic and foreign relevant feature classification system, we proposed a standard feature classification system. In order to validate the applicability of the proposed feature classification system, we evaluated the accuracy with using automatic feature classification based on supervised classification and pre-knowledge hierarchical classification.

Simulation Based Performance Assessment of a LIDAR Data Segmentation Algorithm (라이다데이터 분할 알고리즘의 시뮬레이션 기반 성능평가)

  • Kim, Seong-Joon;Lee, Im-Pyeong
    • Journal of Korean Society for Geospatial Information Science
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    • v.18 no.2
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    • pp.119-129
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    • 2010
  • Many algorithms for processing LIDAR data have been developed for diverse applications not limited to patch segmentation, bare-earth filtering and building extraction. However, since we cannot exactly know the true locations of individual LIDAR points, it is difficult to assess the performance of a LIDAR data processing algorithm. In this paper, we thus attempted the performance assessment of the segmentation algorithm developed by Lee (2006) using the LIDAR data generated through simulation based on sensor modelling. Consequently, based on simulation, we can perform the performance assessment of a LIDAR processing algorithm more objectively and quantitatively with an automatic procedure.

Baggage Recognition in Occluded Environment using Boosting Technique

  • Khanam, Tahmina;Deb, Kaushik
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.11
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    • pp.5436-5458
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    • 2017
  • Automatic Video Surveillance System (AVSS) has become important to computer vision researchers as crime has increased in the twenty-first century. As a new branch of AVSS, baggage detection has a wide area of security applications. Some of them are, detecting baggage in baggage restricted super shop, detecting unclaimed baggage in public space etc. However, in this paper, a detection & classification framework of baggage is proposed. Initially, background subtraction is performed instead of sliding window approach to speed up the system and HSI model is used to deal with different illumination conditions. Then, a model is introduced to overcome shadow effect. Then, occlusion of objects is detected using proposed mirroring algorithm to track individual objects. Extraction of rotational signal descriptor (SP-RSD-HOG) with support plane from Region of Interest (ROI) add rotation invariance nature in HOG. Finally, dynamic human body parameter setting approach enables the system to detect & classify single or multiple pieces of carried baggage even if some portions of human are absent. In baggage detection, a strong classifier is generated by boosting similarity measure based multi layer Support Vector Machine (SVM)s into HOG based SVM. This boosting technique has been used to deal with various texture patterns of baggage. Experimental results have discovered the system satisfactorily accurate and faster comparative to other alternatives.

Material Auto-Transformation Plan using Steal House Method (스틸하우스 공법을 이용한 자재 자동 변환 방안)

  • Han, Jung-Soo;Kim, Gui-Jung
    • The Journal of the Korea Contents Association
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    • v.11 no.5
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    • pp.25-31
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    • 2011
  • In this paper, we propose virtual building construction plans. For this, we compose the construction materials with components and assemble components in pattern. When we change assembled constructions, we can design the building efficiently with patterns if the parts are selected. Also through information analysis of material components or patterns, we can provide information which is necessary to a reconstruction to the designer. Using steal house method, the assembly functions were comprised of a wall, a room, a window, a door, roof etc. Also We explained the materials automatic extraction method which applies steal house.

Moving Object Detection with Rotating Camera Based on Edge Segment Matching (이동카메라 환경에서의 에지 세그먼트 정합을 통한 이동물체 검출)

  • Lee, June-Hyung;Chae, Ok-Sam
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.6
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    • pp.1-12
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    • 2008
  • This paper presents automatic moving object detection method using the rotating camera covering larger area with a single camera. The proposed method is based on the edge segment matching which robust to the dynamic environment with illumination change and background movement. The proposed algorithm presents an edge segment based background panorama image generation method minimizing the distortion due to image stitching, the background image generation method using Generalized Hough Transformation which can reliably register the current image to the panorama image overcoming the stitching distortions, the moving edge segment extraction method that overcome viewpoint difference and distortion. The experimental results show that the proposed method can detect correctly moving object under illumination change and camera vibration.

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