• Title/Summary/Keyword: Image construct

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The Efficient Measurement Method of Buried Heritage by 3D Image Acquisition (3차원 영상취득에 의한 매장문화재의 효율적 측정기법)

  • Lee, Kye-Dong;Lee, Jae-Kee;Jung, Sung-Heuk
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.25 no.2
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    • pp.157-163
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    • 2007
  • Recently, industrialization of a country is accelerated and request of society infrastructure is raised so national land development is activity view. Accordingly, the search for a wide-ranging buried heritage do acted in large construction region. Because the buried heritage get buried in land that it is necessary to the precision search and research for a record and a preservation. Until now, Surveying techniques of a historic site have made status map, profile and cross section map through leveling survey, total-station survey and sketch of specialist. So, to solve problems existing relic survey or drawing making method have using digital camera these researches rapidly and economically obtain stereo image of object and present a technique that constructs 3D image model for digital photogrammetry method. Also, these researches construct 3D image model for record and preservation of a historic site through site test and in 3D and graphical express a historic site and support works that produce other maps if we need it. offer base data of GIS (Geographic Information System) to collect and analyze overall, information of a historic site.

Near-infrared Spectroscopy and an Example of HAM Study;Brain Activation in the Development of Drawing Skills

  • Kobayashi, Harumi;Yasuda, Tetsuya;Suzuki, Satoshi;Takase, Hiroki
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1745-1748
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    • 2005
  • Near-infrared spectroscopy (NIRS) can be used to monitor brain activation by measuring changes in the concentration of oxy- and deoxy-hemoglobin (Hb) by their different spectra in the near-infrared range. Because NIRS is a noninvasive, highly flexible and portable device, it is very suitable to study brain activation when a human repeatedly performs a manipulative task, and possibly provides useful information to construct human adaptive mechatronics (HAM). There is some evidence that the dorsolateral prefrontal cortex (DLPFC) plays a major role in working memory and it is proposed that the use of working memory decreases as a human develops manipulative skills. In the present study, we investigated the activation of the dorsolateral prefrontal cortex (DLPFC) of the brain in Brodmann's areas 9 and 46 in drawing tasks to examine whether NIRS can measure the changes of DLPFC activation as a human develops manipulative skills. Subjects performed a mirror image drawing task and a square drawing task by ones' left hands. In the mirror image task the subject drew following a star shape based on a mirror image of it, but square drawing did not involve mirror image and was estimated to be simpler. The changes of the concentration of oxy-Hb was higher in the mirror image drawing than the square drawing in most subjects. The changes of oxy-Hb decreased as the subject repeated the drawing task in most subjects. In conclusion, The activation of DLPFC measured by NIRS can reflect the brain activity in the development of manipulative skills.

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Multiple Camera-Based Correspondence of Ground Foot for Human Motion Tracking (사람의 움직임 추적을 위한 다중 카메라 기반의 지면 위 발의 대응)

  • Seo, Dong-Wook;Chae, Hyun-Uk;Jo, Kang-Hyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.8
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    • pp.848-855
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    • 2008
  • In this paper, we describe correspondence among multiple images taken by multiple cameras. The correspondence among multiple views is an interesting problem which often appears in the application like visual surveillance or gesture recognition system. We use the principal axis and the ground plane homography to estimate foot of human. The principal axis belongs to the subtracted silhouette-based region of human using subtraction of the predetermined multiple background models with current image which includes moving person. For the calculation of the ground plane homography, we use landmarks on the ground plane in 3D space. Thus the ground plane homography means the relation of two common points in different views. In the normal human being, the foot of human has an exactly same position in the 3D space and we represent it to the intersection in this paper. The intersection occurs when the principal axis in an image crosses to the transformed ground plane from other image. However the positions of the intersection are different depend on camera views. Therefore we construct the correspondence that means the relationship between the intersection in current image and the transformed intersection from other image by homography. Those correspondences should confirm within a short distance measuring in the top viewed plane. Thus, we track a person by these corresponding points on the ground plane. Experimental result shows the accuracy of the proposed algorithm has almost 90% of detecting person for tracking based on correspondence of intersections.

Image Analysis for Discrimination of Neoplastic Cellis in Spatial Frequency Domain (종양세포식별을 위한 공간주파수영역에서의 화상해석)

  • 나철훈;김창원;김현재
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.3
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    • pp.385-396
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    • 1993
  • In this paper, a improved method of digital image analysis required in basic medical science for diagnosis of cells was proposed. The object image was the thyroid gland cell image, and the purpose was automatic discrimination of three classes cells(normal cell, follicular neoplastic cells, and papillary neoplastic cells) by difference of chromatin patterns. To segment the cell nucleus from background, the region segmentation algorithm by edge tracing was proposed. And feature parameter was obtained from discrete Fourier transformation of image. After construct a feature sample group of each cells, experiment of discrimination was executed with any verification cells. As a consequency of using features proposed in this paper, get a better recognition rate(70-90%) than previously reported papers, and this method give shape to get objectivity and fixed quantity in diagnosis of cells, The methods described in this paper be used immediately for discrimination of neoplastic cells.

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Design and Implementation of the System for Automatic Classification of Blood Cell By Image Analysis (영상분석을 통한 혈구자동분류 시스템의 설계 및 구현)

  • Kim, Kyung-Su;Kim, Pan-Koo
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.36C no.12
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    • pp.90-97
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    • 1999
  • Recently, there have been many researches to automate processing and analysing image data in medical field, due to the advance of image processing techniques, the fast communication network and high performance hardware. In this paper, we design and implement the system based on the multi-layer neural network model to be able to analyze, differentiate and count blood cells in the peripheral blood image. To do these, we segment red and white-blood cell in blood image acquired from microscope with CCD(Charge-coupled device) camera and then apply the various feature extraction algorithms to classify. In addition to, we reduce multi-variate feature number using PCA(Principle Component Analysis) to construct more efficient classifier. So, in this paper, we are sure that the proposed system can be applied to a pathological guided system.

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A Study on the Relationship between the Apartment Interior Image Preference ana Personality Types. (아파트 실내 이미지 선호와 성격유형과의 상관성에 관한 연구)

  • 이종희
    • Archives of design research
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    • v.16 no.1
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    • pp.229-240
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    • 2003
  • This study, planed as an idea to promote the degree of the qualitative satisfaction on the residential space and to correspond effectively with the several and characteristic needs, is a try to overcome the limitation which is not to construct with the several plane-plans but the common designs on an apartment, unlike to an individual residence, should be designed for the unidentified persons. For this purpose, 1 set 360 mother group to investigate how to change their degree of the interior-image preference through their Personality Types by the apartment interior image pattern, verified by the pre-study on the real-resident's degree of preference corresponding with MBTI(Myers-Briggs Type Indicator), a Personality Types investigation. This result, leading us to be able to predict the resident's needs of the interior image aspects following the preference of the several products and to be able to supply the products, is being thought to contribute to promote the degree of satisfaction of the resident.

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Salient Object Detection via Multiple Random Walks

  • Zhai, Jiyou;Zhou, Jingbo;Ren, Yongfeng;Wang, Zhijian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.4
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    • pp.1712-1731
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    • 2016
  • In this paper, we propose a novel saliency detection framework via multiple random walks (MRW) which simulate multiple agents on a graph simultaneously. In the MRW system, two agents, which represent the seeds of background and foreground, traverse the graph according to a transition matrix, and interact with each other to achieve a state of equilibrium. The proposed algorithm is divided into three steps. First, an initial segmentation is performed to partition an input image into homogeneous regions (i.e., superpixels) for saliency computation. Based on the regions of image, we construct a graph that the nodes correspond to the superpixels in the image, and the edges between neighboring nodes represent the similarities of the corresponding superpixels. Second, to generate the seeds of background, we first filter out one of the four boundaries that most unlikely belong to the background. The superpixels on each of the three remaining sides of the image will be labeled as the seeds of background. To generate the seeds of foreground, we utilize the center prior that foreground objects tend to appear near the image center. In last step, the seeds of foreground and background are treated as two different agents in multiple random walkers to complete the process of salient object detection. Experimental results on three benchmark databases demonstrate the proposed method performs well when it against the state-of-the-art methods in terms of accuracy and robustness.

Spatially Adaptive Denoising Using Statistical Activity of Wavelet Coefficients (웨이블릿 계수의 통계적 활동성을 이용한 공간 적응 잡음 제거)

  • 엄일규;김유신
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.8C
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    • pp.795-802
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    • 2003
  • It is very important to construct statistical model in order to exactly estimate the signal variance from a noisy image. In order to estimate variance, information of neighboring region is used generally. The size of neighbor region is varied according to the regional characteristics of image. More accurate estimation of edge variance is due to smaller region of neighbor, on the other hands, larger region of neighbor is used to estimate the variance of flat region. By using estimated variance of original image, in general, Wiener filter is constructed, and it is applied to the noisy image. In this paper, we propose a new method for determining the range of neighbors to estimate the variance in wavelet domain. Firstly, a significance map is constructed using the parent-child relationship of wavelet domain. Based on the number of the significant wavelet coefficients, the range of neighbors is determined and then the variance of the original signal is estimated using ML(maximum likelihood method. Experimental results show that the proposed method yields better results than conventional methods for image denoising.

Image Compression Using Edge Map And Multi-Sided Side Match Finite-State Vector Quantization (윤곽선 맵과 다중 면 사이드 매치 유한상태 벡터 양자화를 이용한 영상 압축)

  • Cho, Seong-Hwan;Kim, Eung-Sung
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.8 no.6
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    • pp.1419-1427
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    • 2007
  • In this paper, we propose an algorithm which implements a multi-sided side match finite-state vector quantization(MSMVQ). After extracting the edge information from an image and classifying the image into edge blocks or non-edge blocks, we construct an edge map. We subdivide edge blocks into sixteen classes using discrete cosine transform(DCT) AC coefficients. Based on edge map information, a state codebook is made from the master codebook, and side match calculation is done for two-sided or three-sided current block of image. For reducing transmitted bits, a decision is made whether or not to encode the non-edge blocks among the pre-coded blocks by using the master codebook. Also for reducing allocation bits of codeword indices to decoder, a variable length coder is used. Considering the comparison with side match finite-state vector quantization(SMVQ) and two-sided SMVQ(TSMVQ) algorithm about Zelda, Lenna, Bridge and Peppers image, the new algorithm shows better picture quality than SMVQ and TSMVQ respectively.

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Design and Implementation of a Content-based Color Image Retrieval System based on Color -Spatial Feature (색상-공간 특징을 사용한 내용기반 칼라 이미지 검색 시스템의 설계 및 구현)

  • An, Cheol-Ung;Kim, Seung-Ho
    • Journal of KIISE:Computing Practices and Letters
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    • v.5 no.5
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    • pp.628-638
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    • 1999
  • In this paper, we presents a method of retrieving 24 bpp RGB images based on color-spatial features. For each image, it is subdivided into regions by using similarity of color after converting RGB color space to CIE L*u*v* color space that is perceptually uniform. Our segmentation algorithm constrains the size of region because a small region is discardable and a large region is difficult to extract spatial feature. For each region, averaging color and center of region are extracted to construct color-spatial features. During the image retrieval process, the color and spatial features of query are compared with those of the database images using our similarity measure to determine the set of candidate images to be retrieved. We implement a content-based color image retrieval system using the proposed method. The system is able to retrieve images by user graphic or example image query. Experimental results show that Recall/Precision is 0.80/0.84.