• Title/Summary/Keyword: Image division and merge

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Image Stabilization Scheme for Arbitrary Disturbance (임의의 외란에 대한 영상 안정화)

  • Kwak, Hwy-Kuen
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.9
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    • pp.5750-5757
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    • 2014
  • This paper proposes an image stabilization method for arbitrary disturbances, such as rotation, translation and zoom movement, using the SIFT (Scale Invariant Feature Transform). In addition, image stabilization was carried out using the image division and merge technique when moving objects appear on the scene. Finally, the experimental results showed that the suggested image stabilization scheme produced superior performance compared to the previous ones.

USER BASED IMAGE SEGMENTATION FOR APPLICATION TO SATELLITE IMAGE

  • Im, Hyuk-Soon;Park, Sang-Sung;Shin, Young-Geun;Jang, Dong-Sik
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.126-129
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    • 2008
  • In this paper, we proposed a method extracting an object from background of the satellite image. The image segmentation techniques have been widely studied for the technology to segment image and to synthesis segment object with other images. Proposed algorithm is to perform the edge detection of a selected object using genetic algorithm. We segment region of object based on detection edge using watershed algorithm. We separated background and object in indefinite region using gradual region merge from segment object. And, we make GUI for the application of the proposed algorithm to various tests. To demonstrate the effectiveness of the proposed method, several analysis on the satellite images are performed.

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The Verification of Image Merging for Lumber Scanning System (제재목 화상입력시스템의 화상병합 성능 검증)

  • Kim, Byung Nam;Kim, Kwang Mo;Shim, Kug-Bo;Lee, Hyoung Woo;Shim, Sang-Ro
    • Journal of the Korean Wood Science and Technology
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    • v.37 no.6
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    • pp.556-565
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    • 2009
  • Automated visual grading system of lumber needs correct input image. In order to create a correct image of domestic red pine lumber 3.6 m long feeding on a conveyer, part images were captured using area sensor and template matching algorithm was applied to merge part images. Two kinds of template matching algorithms and six kinds of template sizes were adopted in this operation. Feature extracted method appeared to have more excellent image merging performance than fixed template method. Error length was attributed to a decline of similarity related by difference of partial brightness on a part image, specific pattern and template size. The mismatch part was repetitively generated at the long grain. The best size of template for image merging was $100{\times}100$ pixels. In a further study, assignment of exact template size, preprocessing of image merging for reduction of brightness difference will be needed to improve image merging.

AR monitoring technology for medical convergence (증강현실 모니터링 기술의 의료융합)

  • Lee, Kyung Sook;Lim, Wonbong;Moon, Young Lae
    • Journal of the Korea Convergence Society
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    • v.9 no.2
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    • pp.119-124
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    • 2018
  • The augmented reality(AR) technology enables to acquire various image information at the same time by combining virtual image information with the user's viewpoint. These AR technologies have been used to visualize patients' organs and tissues during surgery and diagnosis in the fields of Image-Guide Operation, Surgical Training, and Image Diagnosis by medical convergence, and provides the most effective surgical methods. In this paper, we study the technical features and application methods of each element technology for medical fusion of AR technology. In the AR technology for medical convergence, display, marker recognition and image synthesis interface technology is essential for efficient medical image. Such AR technology is considered to be a way to drastically improve current medical technology in the fields of image guide surgery, surgical education, and imaging diagnosis.

Localization using Ego Motion based on Fisheye Warping Image (어안 워핑 이미지 기반의 Ego motion을 이용한 위치 인식 알고리즘)

  • Choi, Yun Won;Choi, Kyung Sik;Choi, Jeong Won;Lee, Suk Gyu
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.1
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    • pp.70-77
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    • 2014
  • This paper proposes a novel localization algorithm based on ego-motion which used Lucas-Kanade Optical Flow and warping image obtained through fish-eye lenses mounted on the robots. The omnidirectional image sensor is a desirable sensor for real-time view-based recognition of a robot because the all information around the robot can be obtained simultaneously. The preprocessing (distortion correction, image merge, etc.) of the omnidirectional image which obtained by camera using reflect in mirror or by connection of multiple camera images is essential because it is difficult to obtain information from the original image. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous $360^{\circ}$ panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we extract motion vectors using Lucas-Kanade Optical Flow in preprocessed image. Third, we estimate the robot position and angle using ego-motion method which used direction of vector and vanishing point obtained by RANSAC. We confirmed the reliability of localization algorithm using ego-motion based on fisheye warping image through comparison between results (position and angle) of the experiment obtained using the proposed algorithm and results of the experiment measured from Global Vision Localization System.

MTSAT Satellite Image Features on the Sever Storm Events in Yeongdong Region (영동지역 악기상 사례에 대한 MTSAT 위성 영상의 특징)

  • Kim, In-Hye;Kwon, Tae-Yong;Kim, Deok-Rae
    • Atmosphere
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    • v.22 no.1
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    • pp.29-45
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    • 2012
  • An unusual autumn storm developed rapidly in the western part of the East sea on the early morning of 23 October 2006. This storm produced a record-breaking heavy rain and strong wind in the northern and middle part of the Yeong-dong region; 24-h rainfall of 304 mm over Gangneung and wind speed exceeding 63.7 m $s^{-1}$ over Sokcho. In this study, MTSAT-1R (Multi-fuctional Transport Satellite) water vapor and infrared channel imagery are examined to find out some features which are dynamically associated with the development of the storm. These features may be the precursor signals of the rapidly developing storm and can be employed for very short range forecast and nowcasting of severe storm. The satellite features are summarized: 1) MTSAT-1R Water Vapor imagery exhibited that distinct dark region develops over the Yellow sea at about 12 hours before the occurrence of maximum rainfall about 1100 KST on 23 October 2006. After then, it changes gradually into dry intrusion. This dark region in the water vapor image is closely related with the positive anomaly in 500 hPa Potential Vorticity field. 2) In the Infrared imagery, low stratus (brightness temperature: $0{\sim}5^{\circ}C$) develops from near Bo-Hai bay and Shanfung peninsula and then dissipates partially on the western coast of Korean peninsula. These features are found at 10~12 hours before the maximum rainfall occurrence, which are associated with the cold and warm advection in the lower troposphere. 3) The IR imagery reveals that two convective cloud cells (brightness temperature below $-50^{\circ}C$) merge each other and after merging it grows up rapidly over the western part of East sea at about 5 hours before the maximum rainfall occurrence. These features remind that there must be the upward flow in the upper troposphere and the low-layer convergence over the same region of East sea. The time of maximum growth of the convective cloud agrees well with the time of the maximum rainfall.

A Study on the Hyperspectral Image Classification with the Iterative Self-Organizing Unsupervised Spectral Angle Classification (반복최적화 무감독 분광각 분류 기법을 이용한 하이퍼스펙트럴 영상 분류에 관한 연구)

  • Jo Hyun-Gee;Kim Dae-Sung;Yu Ki-Yun;Kim Yong-Il
    • Korean Journal of Remote Sensing
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    • v.22 no.2
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    • pp.111-121
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    • 2006
  • The classification using spectral angle is a new approach based on the fact that the spectra of the same type of surface objects in RS data are approximately linearly scaled variations of one another due to atmospheric and topographic effects. There are many researches on the unsupervised classification using spectral angle recently. Nevertheless, there are only a few which consider the characteristics of Hyperspectral data. On this study, we propose the ISOMUSAC(Iterative Self-Organizing Modified Unsupervised Spectral Angle Classification) which can supplement the defects of previous unsupervised spectral angle classification. ISOMUSAC uses the Angle Division for the selection of seed points and calculates the center of clusters using spectral angle. In addition, ISOMUSAC perform the iterative merging and splitting clusters. As a result, the proposed algorithm can reduce the time of processing and generate better classification result than previous unsupervised classification algorithms by visual and quantitative analysis. For the comparison with previous unsupervised spectral angle classification by quantitative analysis, we propose Validity Index using spectral angle.