• Title/Summary/Keyword: image vector

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Real-Time Tracking of Human Location and Motion using Cameras in a Ubiquitous Smart Home

  • Shin, Dong-Kyoo;Shin, Dong-Il;Nguyen, Quoc Cuong;Park, Se-Young
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.3 no.1
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    • pp.84-95
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    • 2009
  • The ubiquitous smart home is the home of the future, which exploits context information from both the human and the home environment, providing an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. In this paper, we present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. The system uses four network cameras for real-time human tracking. This paper explains the architecture of the real-time human tracker, and proposes an algorithm for predicting human location and motion. To detect human location, three kinds of images are used: $IMAGE_1$ - empty room image, $IMAGE_2$ - image of furniture and home appliances, $IMAGE_3$ - image of $IMAGE_2$ and the human. The real-time human tracker decides which specific furniture or home appliance the human is associated with, via analysis of three images, and predicts human motion using a support vector machine (SVM). The performance experiment of the human's location, which uses three images, lasted an average of 0.037 seconds. The SVM feature of human motion recognition is decided from the pixel number by the array line of the moving object. We evaluated each motion 1,000 times. The average accuracy of all types of motion was 86.5%.

Perceptual Color Difference based Image Quality Assessment Method and Evaluation System according to the Types of Distortion (인지적 색 차이 기반의 이미지 품질 평가 기법 및 왜곡 종류에 따른 평가 시스템 제안)

  • Lee, Jee-Yong;Kim, Young-Jin
    • Journal of KIISE
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    • v.42 no.10
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    • pp.1294-1302
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    • 2015
  • A lot of image quality assessment metrics that can precisely reflect the human visual system (HVS) have previously been researched. The Structural SIMilarity (SSIM) index is a remarkable HVS-aware metric that utilizes structural information, since the HVS is sensitive to the overall structure of an image. However, SSIM fails to deal with color difference in terms of the HVS. In order to solve this problem, the Structural and Hue SIMilarity (SHSIM) index has been selected with the Hue, Saturation, Intensity (HSI) model as a color space, but it cannot reflect the HVS-aware color difference between two color images. In this paper, we propose a new image quality assessment method for a color image by using a CIE Lab color space. In addition, by using a support vector machine (SVM) classifier, we also propose an optimization system for applying optimal metric according to the types of distortion. To evaluate the proposed index, a LIVE database, which is the most well-known in the area of image quality assessment, is employed and four criteria are used. Experimental results show that the proposed index is more consistent with the other methods.

Generating a Stereoscopic Image from a Monoscopic Camera (단안 카메라를 이용한 입체영상 생성)

  • Lee, Dong-Woo;Lee, Kwan-Wook;Kim, Man-Bae
    • Journal of Broadcast Engineering
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    • v.17 no.1
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    • pp.17-25
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    • 2012
  • In this paper, we propose a method of producing a stereoscopic image from multiple images captured from a monoscopic camera. By translating a camera in the horizontal direction, left and right images are chosen among N captured images. For this, image edges are extracted and a rotational angle is estimated from edge orientation. Also, a translational vector is also estimated from the correlation of projected image data. Then, two optimal images are chosen and subsequently compensated using the rotational angle as well as the translational vector in order to make a satisfactory stereoscopic image. The proposed method was performed on thirty-two test image set. The subjective visual fatigue test was carried out to validate the 3D quality of stereoscopic images. In terms of visual fatigue, the 3D satisfaction ratio reached approximately 84%.

Designation for Change Detection of Building Objects in Urban Area in High-Resolution Satellite Image (고정밀 위성영상에서 도심지역 건물변화 탐지를 위한 중첩방법)

  • 이승희;박성모;이준환;김준철
    • Korean Journal of Remote Sensing
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    • v.19 no.4
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    • pp.319-328
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    • 2003
  • The automatic analysis of high-resolution satellite image is important in cartography, surveillance, exploiting resources etc. However, the automatic analysis of high resolution satellite image in the urban area has lots of difficulty including a shadow, the difference of illumination with time, the complexity of image so that the present techniques are seemed to be impossible to resolve. This paper proposes a new way of change detection of building objects in urban area, in which the objects in digital vector map are designated and superimposed on the the high-resolution satellite image. The proposed way makes the buildings on the vector map parameterize, and searches them in the preprocessed high-resolution satellite image by using generalized Hough transform. The designated building objects are overlaid on the satellite image and the result can help to search the changes in building objects rapidly.

Feature Extraction Based on GRFs for Facial Expression Recognition

  • Yoon, Myoong-Young
    • Journal of Korea Society of Industrial Information Systems
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    • v.7 no.3
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    • pp.23-31
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    • 2002
  • In this paper we propose a new feature vector for recognition of the facial expression based on Gibbs distributions which are well suited for representing the spatial continuity. The extracted feature vectors are invariant under translation rotation, and scale of an facial expression imege. The Algorithm for recognition of a facial expression contains two parts: the extraction of feature vector and the recognition process. The extraction of feature vector are comprised of modified 2-D conditional moments based on estimated Gibbs distribution for an facial image. In the facial expression recognition phase, we use discrete left-right HMM which is widely used in pattern recognition. In order to evaluate the performance of the proposed scheme, experiments for recognition of four universal expression (anger, fear, happiness, surprise) was conducted with facial image sequences on Workstation. Experiment results reveal that the proposed scheme has high recognition rate over 95%.

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On Development of the GIS Application Based on Satellite Images (위성영상을 기반으로 한 GIS 응용 시스템 개발)

  • 양인태;최영재
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.22 no.1
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    • pp.1-9
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    • 2004
  • Until comparatively lately the use of vector data is the main current in GIS fields. Vector data have many advantages such as easy of scale change, small data volume and so on. But it also has some weak point that can't apply real world. The other hand the satellite images have strong point that can apply real world actually. Recently rapid progress of computer capacity and processing velocity is the current trend of the times. Therefore in this study I intend to develop GIS application based on satellite images with vector data and raster data altogether. This system is developed by using Visual C++ in the personal computer and MS Access's MDB far database management. The LANDSAT, KOMPSAT and IKONOS satellite image database were used in this study. Also, we are studied to set up scale for screen display according to spatial resolution.

Vehicle License Plate Recognition System using DCT and LVQ (DCT와 LVQ를 이용한 차량번호판 인식 시스템)

  • 한수환
    • Journal of Intelligence and Information Systems
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    • v.8 no.1
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    • pp.15-25
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    • 2002
  • This paper proposes a vehicle license plate recognition system, which has relatively a simple structure and is highly tolerant of noise, by using the DCT(Discrete Cosine Transform) coefficients extracted from the character region of a license plate and the LVQ(Learning Vector Quantization) neural network. The image of a license plate is taken from a captured vehicle image based on RGB color information, and the character region is derived by the histogram of the license plate and the relative position of individual characters in the plate. The feature vector obtained by the DCT of extracted character region is utilized as an input to the LVQ neural classifier fur the recognition process. In the experiment, 109 vehicle images captured under various types of circumstances were tested with the proposed method, and the relatively high extraction rate of license plates and recognition rate were achieved.

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Motion Estimation and Machine Learning-based Wind Turbine Monitoring System (움직임 추정 및 머신 러닝 기반 풍력 발전기 모니터링 시스템)

  • Kim, Byoung-Jin;Cheon, Seong-Pil;Kang, Suk-Ju
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.10
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    • pp.1516-1522
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    • 2017
  • We propose a novel monitoring system for diagnosing crack faults of the wind turbine using image information. The proposed method classifies a normal state and a abnormal state for the blade parts of the wind turbine. Specifically, the images are input to the proposed system in various states of wind turbine rotation. according to the blade condition. Then, the video of rotating blades on the wind turbine is divided into several image frames. Motion vectors are estimated using the previous and current images using the motion estimation, and the change of the motion vectors is analyzed according to the blade state. Finally, we determine the final blade state using the Support Vector Machine (SVM) classifier. In SVM, features are constructed using the area information of the blades and the motion vector values. The experimental results showed that the proposed method had high classification performance and its $F_1$ score was 0.9790.

The Change of Coastline through High Pass Filter using ASTER Images (ASTER영상을 이용한 고주파 필터에 의한 해안선 변화 분석)

  • Choi, Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.6
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    • pp.1279-1284
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    • 2012
  • This study is about the change of coastline through using ASTER images. ASTER image is a sensor loaded in earth resources satellite shoot in Japan on Dec. 1999. It has 15m, 30m, 90m coastline, three sensors of VNIR, TIR and WIR, therefore it's possible to obtain more information on the Earth than the existing satellite images cause it contains various a wavelength range in spite of relatively economic image. The coastline is changed according to topography shape because it's strongly localized. Besides, it's one of the most important factors in MGIS(Marine Geographic Information System). Therefore, this study is accomplished by analysing variation after abstraction the coastline automatically by Vector Line from ASTER satellite images. The study result will be used as an important basic data when analysis the change of e coastline hereafter.

A Fault Severity Index for Stator Winding Faults Detection in Vector Controlled PM Synchronous Motor

  • Hadef, M.;Djerdir, A.;Ikhlef, N.;Mekideche, M.R.;N'diaye, A. O.
    • Journal of Electrical Engineering and Technology
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    • v.10 no.6
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    • pp.2326-2333
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    • 2015
  • Stator turn faults in permanent magnet synchronous motors (PMSMs) are more dangerous than those in induction motors (IMs) because of the presence of spinning rotor magnets that can be turned off at will. Condition monitoring and fault detection and diagnosis of the PMSM have been receiving a growing amount of attention among scientists and engineers in the past few years. The aim of this study is to propose a new detection technique of stator winding faults in a three-phase PMSM. This technique is based on the image analysis and recognition of the stator current Concordia patterns, and will allow the identification of turn faults in the stator winding as well as its correspondent fault index severity. A test bench of a vector controlled PMSM motor behaviors under short circuited turn in two phases stator windings has been built. Some experimental results of the phase to phase short circuits have been performed for diagnosis purpose.