• Title/Summary/Keyword: Area Based Matching

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KNN/ANN Hybrid Location Determination Algorithm for Indoor Location Base Service (실내 위치기반서비스를 위한 KNN/ANN Hybrid 측위 결정 알고리즘)

  • Lee, Jang-Jae;Jung, Min-A;Lee, Seong-Ro;Song, Iick-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.2
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    • pp.109-115
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    • 2011
  • As fingerprinting method, k-nearest neighbor(KNN) has been widely applied for indoor location in wireless location area networks(WLAN), but its performance is sensitive to number of neighbors k and positions of reference points(RPs). So artificial neural network(ANN) clustering algorithm is applied to improve KNN, which is the KNN/ANN hybrid algorithm presented in this paper. For any pattern matching based algorithm in WLAN environment, the characteristics of signal to noise ratio(SNR) to multiple access points(APs) are utilized to establish database in the training phase, and in the estimation phase, the actual two dimensional coordinates of mobile unit(MU) are estimated based on the comparison between the new recorded SNR and fingerprints stored in database. In the proposed algorithm, through KNN, k RPs are firstly chosen as the data samples of ANN based on SNR. Then, the k RPs are classified into different clusters through ANN based on SNR. Experimental results indicate that the proposed KNN/ANN hybrid algorithm generally outperforms KNN algorithm when the locations error is less than 2m.

Distracted Driver Detection and Characteristic Area Localization by Combining CAM-Based Hierarchical and Horizontal Classification Models (CAM 기반의 계층적 및 수평적 분류 모델을 결합한 운전자 부주의 검출 및 특징 영역 지역화)

  • Go, Sooyeon;Choi, Yeongwoo
    • KIPS Transactions on Software and Data Engineering
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    • v.10 no.11
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    • pp.439-448
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    • 2021
  • Driver negligence accounts for the largest proportion of the causes of traffic accidents, and research to detect them is continuously being conducted. This paper proposes a method to accurately detect a distracted driver and localize the most characteristic parts of the driver. The proposed method hierarchically constructs a CNN basic model that classifies 10 classes based on CAM in order to detect driver distration and 4 subclass models for detailed classification of classes having a confusing or common feature area in this model. The classification result output from each model can be considered as a new feature indicating the degree of matching with the CNN feature maps, and the accuracy of classification is improved by horizontally combining and learning them. In addition, by combining the heat map results reflecting the classification results of the basic and detailed classification models, the characteristic areas of attention in the image are found. The proposed method obtained an accuracy of 95.14% in an experiment using the State Farm data set, which is 2.94% higher than the 92.2%, which is the highest accuracy among the results using this data set. Also, it was confirmed by the experiment that more meaningful and accurate attention areas were found than the results of the attention area found when only the basic model was used.

Gaze Tracking Using a Modified Starburst Algorithm and Homography Normalization (수정 Starburst 알고리즘과 Homography Normalization을 이용한 시선추적)

  • Cho, Tai-Hoon;Kang, Hyun-Min
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.5
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    • pp.1162-1170
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    • 2014
  • In this paper, an accurate remote gaze tracking method with two cameras is presented using a modified Starburst algorithm and honography normalization. Starburst algorithm, which was originally developed for head-mounted systems, often fails in detecting accurate pupil centers in remote tracking systems with a larger field of view due to lots of noises. A region of interest area for pupil is found using template matching, and then only within this area Starburst algorithm is applied to yield pupil boundary candidate points. These are used in improved RANSAC ellipse fitting to produce the pupil center. For gaze estimation robust to head movement, an improved homography normalization using four LEDs and calibration based on high order polynomials is proposed. Finally, it is shown that accuracy and robustness of the system is improved using two cameras rather than one camera.

Development of the Prototype of Integrated Information System for Conflation and Utilization of Land and Building Information (토지·건물정보의 융복합 및 활용을 통한 통합정보시스템 프로토타입 개발)

  • Park, Woo-Jin;Jeong, Dong-Hoon;Park, Jung-Hee
    • Journal of Cadastre & Land InformatiX
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    • v.46 no.2
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    • pp.341-356
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    • 2016
  • Land information and building information have highest utilization and importance in real estate and city administration area. However, providing integrated information service was difficult because conflation and integrative utilization was not easy. In this study, necessity of integrated information system, direction of integration, method of conflation and design of integrated system for land and building information are presented. In addition, the prototype system is developed and possibility of application of integrated information is proposed. For this purpose, current situation of management of land and building information was analyzed. Based on the analysis, matching and conflation processes among spatial and attribute data were applied to land and building information. Using integrated land building information DB, integrated information system and functions were designed and the prototype system was constructed. At last, information service examples in real estate and city administration area were suggested through system operation by LX.

A study on the fabrication of Y-branch for optical power distribution and its coupling properties with optical fiber (광분배를 위한 Y-branch 제작과 광파이버와의 결합특성에 관한 연구)

  • 김상덕;박수봉;윤중현;이재규;김종빈
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.12
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    • pp.3277-3285
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    • 1996
  • In this paper, w designed an opical power distribution device for application to an optical switching and an optical subscriber loop. We fabricated PSG thin film by LPCVD. Based on the measured index of fabricted thin film, rib-type waveguide was transformed to two-dimension by the effective index method and we simulated dispersion property to find asingle-mode condition. We found that the optimum design parameters of rib-type waveguide are:cladding layer of 3.mu.m, core layer of 3.mu.m, buffer layer of 10.mu.m, and core width of 4.mu.m. Each side of the guiding region was etched down to 4.mu.m to shape the core. We used these optimum parameters of the rib-type waveguide with branching angle of 0.5.deg. and simulted the Y-branch waveguide by the BPM simulation. Numerical loss in branching area was claculated to be 0.1581dB and equal to the total loss of the Y-branch. The loss of the fabricated Y-branch waveguide on PSG film ws 1.6dB at .lambda.=1.3.mu.m before annealing but was 1.2dB after annealing at 1000.deg. C for 10 minutes. Consequently, the loss of branching area from 3000.mu.m to 6000.mu.m in the z-direction was 0.8dB, and single-mode propagation was confirmed by measuring the near field pattern. For coupling the fabricated Y-branch waveguide with an optical fiber, we fabricated V-groove which was used as the upholder of optical fiber. An etching angle was 54.deg. and the width and depth of guiding groove was 150.mu.m, 70.mu.m, respectively. The optical fiber is inserted onto V-groove. Both the Y-branch and V-groove were connected through the index matching oil. Coupling loss after connecting Y-branch and the optical fiber on V-groove was 0.34dB and that after injecting index mateching oil was 0.14dB.

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Image Stitching Using Normalized Cross-Correlation and the Thresholding Method in a Fluorescence Microscopy Image of Brain Tumor Cells (정규 상호상관도 및 이진화 기법을 이용한 뇌종양 세포의 형광 현미경 영상 스티칭)

  • Seo, Ji Hyun;Kang, Mi-Sun;Kim, Hyun-jung;Kim, Myoung-Hee
    • Journal of Korea Multimedia Society
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    • v.20 no.7
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    • pp.979-985
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    • 2017
  • This paper, which covers a fluorescence microscopy image of brain tumor cells, looks at drug reactions by treating different types and concentrations of drugs on a plate of $24{\times}16$ wells. Due to the limitation of the field of view, a well was taken into 9 field images, and each has an overlapping area with its neighboring fields. To analyze more precisely, image stitching is needed. The basic method is finding a similar area using normalized cross-correlation (NCC). The problem is that some overlapping areas may not have any duplicated cells that help to find the matching point. In addition, the cell objects have similar sizes and shapes, which makes distinguishing them difficult. To avoid calculating similarity between blank areas and roughly distinguishing different cells, thresholding is added. The thresholding method classifies background and cell objects based on fixed thresholds and finds the location of the first seen cell. After getting its location, NCC is used to find the best correlation point. The results are compared with a simple boundary stitched image. Our proposed method stitches images that are connected in a grid form without collision, selecting the best correlation point among areas that contain overlapping cells and ones without it.

A Cross-Diamond-Triangle Search Algorithm for Fast Block-Matching Motion Estimation (고속 블록 정합 움직임 측정을 위한 십자-다이아몬드-삼각 탐색 알고리즘)

  • Kim, Seong-Hoon;Shin, Jae-Min;Oh, Seoung-Jun;Ahn, Chang-Beom;Park, Ho-Chong;Sim, Dong-Gyu
    • Journal of Broadcast Engineering
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    • v.10 no.3
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    • pp.357-371
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    • 2005
  • In this Paper, we propose a new motion search algorithm called CDTS (Cross-Diamond-Triangle Search algorithm) that uses optimal search pattern according to the position of a search area to improve the performance of CDS(Cross-Diamond Search algorithm) as well as CDHSs(Cross-Diamond-Hexagonal Searches algorithms). We analyze motion distributions in various test video sequences to apply optimal search pattern according to a position of search area. Based on the result of this analysis, we propose a new triangle-shaped search pattern whose structure is asymmetric while previous search patterns are generally symmetric in conventional algorithms. In CDTS, we apply cross- and diamond-shaped search patterns to central search areas, and triangle- and diamond-shaped patterns to the other areas. Applying CDTS to test video sequences, the proposed scheme can reduce search points more than CDS and CDHSs by 16.22$\%$ and 3.09$\%$, respectively, without any visual quality degradation.

SHADOW EXTRACTION FROM ASTER IMAGE USING MIXED PIXEL ANALYSIS

  • Kikuchi, Yuki;Takeshi, Miyata;Masataka, Takagi
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.727-731
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    • 2003
  • ASTER image has some advantages for classification such as 15 spectral bands and 15m ${\sim}$ 90m spatial resolution. However, in the classification using general remote sensing image, shadow areas are often classified into water area. It is very difficult to divide shadow and water. Because reflectance characteristics of water is similar to characteristics of shadow. Many land cover items are consisted in one pixel which is 15m spatial resolution. Nowadays, very high resolution satellite image (IKONOS, Quick Bird) and Digital Surface Model (DSM) by air borne laser scanner can also be used. In this study, mixed pixel analysis of ASTER image has carried out using IKONOS image and DSM. For mixed pixel analysis, high accurated geometric correction was required. Image matching method was applied for generating GCP datasets. IKONOS image was rectified by affine transform. After that, one pixel in ASTER image should be compared with corresponded 15×15 pixel in IKONOS image. Then, training dataset were generated for mixed pixel analysis using visual interpretation of IKONOS image. Finally, classification will be carried out based on Linear Mixture Model. Shadow extraction might be succeeded by the classification. The extracted shadow area was validated using shadow image which generated from 1m${\sim}$2m spatial resolution DSM. The result showed 17.2% error was occurred in mixed pixel. It might be limitation of ASTER image for shadow extraction because of 8bit quantization data.

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Accuracy Estimation of Electro-optical Camera (EOC) on KOMPSAT-1

  • Park, Woon-Yong;Hong, Sun-Houn;Song, Youn-Kyung
    • Korean Journal of Geomatics
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    • v.2 no.1
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    • pp.47-55
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    • 2002
  • Remote sensing is the science and art of obtaining information about an object, area or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation./sup 1)/ EOC (Electro -Optical Camera) sensor loaded on the KOMPSAT-1 (Korea Multi- Purpose Satellite-1) performs the earth remote sensing operation. EOC can get high-resolution images of ground distance 6.6m during photographing; it is possible to get a tilt image by tilting satellite body up to 45 degrees at maximum. Accordingly, the device developed in this study enables to obtain images by photographing one pair of tilt image for the same point from two different planes. KOMPSAT-1 aims to obtain a Korean map with a scale of 1:25,000 with high resolution. The KOMPSAT-1 developed automated feature extraction system based on stereo satellite image. It overcomes the limitations of sensor and difficulties associated with preprocessing quite effectively. In case of using 6, 7 and 9 ground control points, which are evenly spread in image, with 95% of reliability for horizontal and vertical position, 3-dimensional positioning was available with accuracy of 6.0752m and 9.8274m. Therefore, less than l0m of design accuracy in KOMPSAT-1 was achieved. Also the ground position error of ortho-image, with reliability of 95%, is 17.568m. And elevation error showing 36.82m was enhanced. The reason why elevation accuracy was not good compared with the positioning accuracy used stereo image was analyzed as a problem of image matching system. Ortho-image system is advantageous if accurate altitude and production of digital elevation model are desired. The Korean map drawn on a scale of 1: 25,000 by using the new technique of KOMPSAT-1 EOC image adopted in the present study produces accurate result compared to existing mapping techniques involving high costs with less efficiency.

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Automatic Container Placard Recognition System (컨테이너 플래카드 자동 인식 시스템)

  • Heo, Gyeongyong;Lee, Imgeun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.6
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    • pp.659-665
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    • 2019
  • Various placards are attached to the surface of a container depending on the risk of the cargo loaded. Containers with dangerous goods should be managed separately from ordinary containers. Therefore, as part of the port automation system, there is a demand for automatic recognition of placards. In this paper, proposed is a system that automatically extracts the placard area based on the shape features of the placard and recognizes the contents in it. Various distortions can be caused by the surface curvature of the container, therefore, attention should be paid to the area extraction and recognition process. The proposed system can automatically extract the region of interest and recognize the placard using the feature that the placard is diamond shaped and the class number is written just above the lower vertex. When the proposed system is applied to real images, the placard can be recognized without error, and the used techniques can be applied to various image analysis systems.