• Title/Summary/Keyword: Point-extraction

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3D BUILDING INFORMATION EXTRACTION FROM A SINGLE QUICKBIRD IMAGE

  • Kim, Hye-Jin;Han, Dong-Yeob;Kim, Yong-Il
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.409-412
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    • 2006
  • Today's commercial high resolution satellite imagery such as IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Recognizing this potential use of high resolution satellite imagery, KARI is performing a project for developing Korea multipurpose satellite 3(KOMPSAT-3). Therefore, it is necessary to develop techniques for various GIS applications of KOMPSAT-3, using similar high resolution satellite imagery. As fundamental studies for this purpose, we focused on the extraction of 3D spatial information and the update of existing GIS data from QuickBird imagery. This paper examines the scheme for rectification of high resolution image, and suggests the convenient semi-automatic algorithm for extraction of 3D building information from a single image. The algorithm is based on triangular vector structure that consists of a building bottom point, its corresponding roof point and a shadow end point. The proposed method could increase the number of measurable building, and enhance the digitizing accuracy and the computation efficiency.

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Defect Cell Extraction for TFT-LCD Auto-Repair System (TFT-LCD 자동 수선시스템에서 결함이 있는 셀을 자동으로 추출하는 방법)

  • Cho, Jae-Soo;Ha, Gwang-Sung;Lee, Jin-Wook;Kim, Dong-Hyun;Jeon, Edward
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.5
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    • pp.432-437
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    • 2008
  • This paper proposes a defect cell extraction algorithm for TFT-LCD auto-repair system. Auto defect search algorithm and automatic defect cell extraction method are very important for TFT-LCD auto repair system. In the previous literature[1], we proposed an automatic visual inspection algorithm of TFT-LCD. Based on the inspected information(defect size and defect axis, if defect exists) by the automatic search algorithm, defect cells should be extracted from the input image for the auto repair system. For automatic extraction of defect cells, we used a novel block matching algorithm and a simple filtering process in order to find a given reference point in the LCD cell. The proposed defect cell extraction algorithm can be used in all kinds of TFT-LCD devices by changing a stored template which includes a given reference point. Various experimental results show the effectiveness of the proposed method.

Tow-stage Extraction of Milk Fat by Supercritical Carbon Dioxide

  • Sangbin Lim;Jwa, Mi-Kyung;Kwak, Hae-Soo
    • Preventive Nutrition and Food Science
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    • v.2 no.3
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    • pp.202-206
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    • 1997
  • To develop mil fat fractions with desirable physico-chemical properties, anhydrous milk fat (AMF) was fractionated by one- and two-stage extractions using supercritical $CO_2$(SC-$CO_2$). Tow-stage extraction of AMF was performed by first producing tow fractions, an extract and a residue at 4$0^{\circ}C$/241bar, which were subsequently used as the feed for an extraction at 6$0^{\circ}C$/241bar and 4$0^{\circ}C$/345bar, and separated into five and four fractions, respectively, based one extraction time. These fractions were quantified and analyzed for fatty acids and physico-chemical properties. SHort-chain (C4~C8) fatty acids in extract fractions from an extract were 200~150% compared with those of the original AF. Long-chain (C14~C18) fatty acids in extract fractions from a residue were 118~141%. The ratio of unsaturated fatty acids in the residue fraction was 131%. Melting point ranged from 22 to 43$^{\circ}C$, iodine value 21.8 to 36.9, and saponification value 255 to 221 in the extract and residue fractions. SC-$CO_2$ fractionation of AMF by two-stage extraction offers the possibility of developing ractions with discrete fatty acid compositions and physico-chemical properties such as melting point, iodine value and saponification value.

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A Method to Adjust Cyclic Signal Length Using Time Invariant Feature Point Extraction and Matching(TIFEM) (시불변 특징점 추출 및 정합을 이용한 주기 신호의 길이 보정 기법)

  • Han, A-Hyang;Park, Cheong-Sool;Kim, Sung-Shick;Baek, Jun-Geol
    • Journal of the Korea Society for Simulation
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    • v.19 no.4
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    • pp.111-122
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    • 2010
  • In this study, a length adjustment algorithm for cyclic signals in manufacturing process using Time Invariant Feature point Extraction and Matching(TIFEM) is proposed. In order to precisely compensate the length of cyclic signals which have irregular length in the middle of signal as well as in the full length more feature points are needed. The extracted feature must involve information about the pattern of signal and should have invariant properties on time and scale. The proposed TIFEM algorithm extracts features having the intrinsic properties of the signal characteristics at first. By using those extracted features, feature vector is constructed for each time point. Among those extracted features, the only effective features are filtered and are chosen such as basis for the length adjustment. And then the partial length adjustment is performed by matching feature points. To verify the performance of the proposed algorithm, the experiments were performed with the experimental data mimicking the three kinds of signals generated from the actual semiconductor process.

Image Feature Extraction Using Independent Component Analysis of Hybrid Fixed Point Algorithm (조합형 Fixed Point 알고리즘의 독립성분분석을 이용한 영상의 특징추출)

  • Cho, Yong-Hyun;Kang, Hyun-Koo
    • Journal of the Korean Society of Industry Convergence
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    • v.6 no.1
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    • pp.23-29
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    • 2003
  • This paper proposes an efficient feature extraction of the images by using independent component analysis(ICA) based on neural networks of the hybrid learning algorithm. The proposed learning algorithm is the fixed point(FP) algorithm based on Newton method and moment. The Newton method, which uses to the tangent line for estimating the root of function, is applied for fast updating the inverse mixing matrix. The moment is also applied for getting the better speed-up by restraining an oscillation due to compute the tangent line. The proposed algorithm has been applied to the 10,000 image patches of $12{\times}12$-pixel that are extracted from 13 natural images. The 144 features of $12{\times}12$-pixel and the 160 features of $16{\times}16$-pixel have been extracted from all patches, respectively. The simulation results show that the extracted features have a localized characteristics being included in the images in space, as well as in frequency and orientation. And the proposed algorithm has better performances of the learning speed than those using the conventional FP algorithm based on Newton method.

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The Study on Prediction of Hot Water Extraction in a Thermal Energy Storage System (축열시스템의 온수이용 예측에 관한 연구)

  • Cho, W.;Pak, E.T.
    • Solar Energy
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    • v.18 no.3
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    • pp.71-80
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    • 1998
  • In thermal energy storage system, energy collected from many types of heat source is stored in a storage tank and then supply to load for demand. Lately, practical use of thermal energy storage system and attention to essential use of energy have been increased. From this point of view, especially, a study about the energy extraction process from a storage tank is necessary. So in this study, useful rate of hot water and hot water extraction efficiency was analysed respect to dynamic and geometric parameters dominating the hot water extraction process.

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Robust Feature Extraction and Tracking Algorithm Using 2-dimensional Wavelet Transform (2차원 웨이브릿 변환을 이용한 강건한 특징점 추출 및 추적 알고리즘)

  • Jang, Sung-Kun;Suk, Jung-Youp
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.405-406
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    • 2007
  • In this paper, we propose feature extraction and tracking algorithm using multi resolution in 2-dimensional wavelet domain. Feature extraction selects feature points using 2-level wavelet transform in interested region. Feature tracking estimates displacement between current frame and next frame based on feature point which is selected feature extraction algorithm. Experimental results show that the proposed algorithm confirmed a better performance than the existing other algorithms.

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Surface Extraction from Point-Sampled Data through Region Growing

  • Vieira, Miguel;Shimada, Kenji
    • International Journal of CAD/CAM
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    • v.5 no.1
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    • pp.19-27
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    • 2005
  • As three-dimensional range scanners make large point clouds a more common initial representation of real world objects, a need arises for algorithms that can efficiently process point sets. In this paper, we present a method for extracting smooth surfaces from dense point clouds. Given an unorganized set of points in space as input, our algorithm first uses principal component analysis to estimate the surface variation at each point. After defining conditions for determining the geometric compatibility of a point and a surface, we examine the points in order of increasing surface variation to find points whose neighborhoods can be closely approximated by a single surface. These neighborhoods become seed regions for region growing. The region growing step clusters points that are geometrically compatible with the approximating surface and refines the surface as the region grows to obtain the best approximation of the largest number of points. When no more points can be added to a region, the algorithm stores the extracted surface. Our algorithm works quickly with little user interaction and requires a fraction of the memory needed for a standard mesh data structure. To demonstrate its usefulness, we show results on large point clouds acquired from real-world objects.

Feature Extraction for Endoscopic Image by using the Scale Invariant Feature Transform(SIFT) (SIFT를 이용한 내시경 영상에서의 특징점 추출)

  • Oh, J.S.;Kim, H.C.;Kim, H.R.;Koo, J.M.;Kim, M.G.
    • Proceedings of the KIEE Conference
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    • 2005.10b
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    • pp.6-8
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    • 2005
  • Study that uses geometrical information in computer vision is lively. Problem that should be preceded is matching problem before studying. Feature point should be extracted for well matching. There are a lot of methods that extract feature point from former days are studied. Because problem does not exist algorithm that is applied for all images, it is a hot water. Specially, it is not easy to find feature point in endoscope image. The big problem can not decide easily a point that is predicted feature point as can know even if see endoscope image as eyes. Also, accuracy of matching problem can be decided after number of feature points is enough and also distributed on whole image. In this paper studied algorithm that can apply to endoscope image. SIFT method displayed excellent performance when compared with alternative way (Affine invariant point detector etc.) in general image but SIFT parameter that used in general image can't apply to endoscope image. The gual of this paper is abstraction of feature point on endoscope image that controlled by contrast threshold and curvature threshold among the parameters for applying SIFT method on endoscope image. Studied about method that feature points can have good distribution and control number of feature point than traditional alternative way by controlling the parameters on experiment result.

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Development of an Algorithm for Automatic Extraction of Lower Body Landmarks Using Grasshopper Programming Language (Grasshopper 프로그래밍 기반 3D 인체형상의 하반신 기준점 자동탐색 알고리즘 설계)

  • Eun Joo Ryu;Hwa Kyung Song
    • Journal of the Korean Society of Clothing and Textiles
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    • v.47 no.1
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    • pp.171-190
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    • 2023
  • This study aims to develop algorithms for automatic extraction landmarks from the lower body of women aged 20-54 using the Grasshopper programming language, based on 3D scan data in the 8th SizeKorea dataset. First, 11 landmarks were defined using the morphological features of 3D body surfaces and clothing applications, from which automatic landmark extraction algorithms were developed. To verify the accuracy of the algorithm, this study developed an additional algorithm that could automatically measure 16 items, and algorithm-derived measurements and SizeKorea measurements were compared using paired t-test analysis. The statistical differences between the scan-derived measurements and the SizeKorea measurements were compared, with an allowable tolerance of ISO 20685-1:2018. This study found that the algorithm successfully identified most items except for the crotch point and gluteal fold point. In the case of landmarks with significant differences, the algorithms were modified. This study was significant because scan editing, landmark search, and measurement extraction were successfully performed in one interface, and the developed algorithm has a high efficiency and strong adaptability.