• Title/Summary/Keyword: 검출 모델

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A Study on Hand-signal Recognition System in 3-dimensional Space (3차원 공간상의 수신호 인식 시스템에 대한 연구)

  • 장효영;김대진;김정배;변증남
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.41 no.3
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    • pp.103-114
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    • 2004
  • This paper deals with a system that is capable of recognizing hand-signals in 3-dimensional space. The system uses 2 color cameras as input devices. Vision-based gesture recognition system is known to be user-friendly because of its contact-free characteristic. But as with other applications using a camera as an input device, there are difficulties under complex background and varying illumination. In order to detect hand region robustly from a input image under various conditions without any special gloves or markers, the paper uses previous position information and adaptive hand color model. The paper defines a hand-signal as a combination of two basic elements such as 'hand pose' and 'hand trajectory'. As an extensive classification method for hand pose, the paper proposes 2-stage classification method by using 'small group concept'. Also, the paper suggests a complementary feature selection method from images from two color cameras. We verified our method with a hand-signal application to our driving simulator.

Thermal Infrared Image Enhancement Method Based on Retinex (Retinex 처리에 기반한 적외선 열상 이미지의 화질 개선)

  • Lee, Won-Seok;Kim, Kyoung-Hee;Lee, Sang-Won
    • 전자공학회논문지 IE
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    • v.48 no.2
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    • pp.32-39
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    • 2011
  • The output image of the uncooled thermal infrared camera is difficult the identification of target because of the limited dynamic range and the various noises. Retinex algorithm based on the theory of the human visual perception is known to be effective contrast enhancement technique. However, the image quality is insufficient when it is adopted to the narrow dynamic range image as the infrared image. In this paper, we propose the revised retinex algorithm to enhance the contrast of the infrared image. To improve the contrast enhancement performance, we designed the new dynamic range compression function instead of log function. To reduce the noise and compensate the loss of edge, we added the contrast compensation procedure in the MSR image generation process. According to the output picture comparing and numerical analysis, the proposed algorithm shows the better contrast enhancement performance and the more suitable method for the infrared image enhancement.

Noise Modeling for CR Images of High-strength Materials (고강도매질 CR 영상의 잡음 모델링)

  • Hwang, Jung-Won;Hwang, Jae-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.5
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    • pp.95-102
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    • 2008
  • This paper presents an appropriate approach for modeling noise in Computed Radiography(CR) images of high strength materials. The approach is specifically designed for types of noise with the statistical and nonlinear properties. CR images Ere degraded even before they are encoded by computer process. Various types of noise often contribute to contaminate radiography image, although they are detected on digitalization. Quantum noise, which is Poisson distributed, is a shot noise, but the photon distribution on Image Plate(IP) of CR system is not always Poisson process. The statistical properties are relative and case-dependant due to its material characteristics. The usual assumption of a distribution of Poisson, binomial and Gaussian statistics are considered. Nonlinear effect is also represented in the process of statistical noise model. It leads to estimate the noise variance in regions from high to low intensity, specifying analytical model. The analysis approach is tested on a database of steel tube step-wedge CR images. The results are available for the comparative parameter studies which measure noise coherence, distribution, signal/noise ratios(SNR) and nonlinear interpolation.

A Driver's Condition Warning System using Eye Aspect Ratio (눈 영상비를 이용한 운전자 상태 경고 시스템)

  • Shin, Moon-Chang;Lee, Won-Young
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.2
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    • pp.349-356
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    • 2020
  • This paper introduces the implementation of a driver's condition warning system using eye aspect ratio to prevent a car accident. The proposed driver's condition warning system using eye aspect ratio consists of a camera, that is required to detect eyes, the Raspberrypie that processes information on eyes from the camera, buzzer and vibrator, that are required to warn the driver. In order to detect and recognize driver's eyes, the histogram of oriented gradients and face landmark estimation based on deep-learning are used. Initially the system calculates the eye aspect ratio of the driver from 6 coordinates around the eye and then gets each eye aspect ratio values when the eyes are opened and closed. These two different eye aspect ratio values are used to calculate the threshold value that is necessary to determine the eye state. Because the threshold value is adaptively determined according to the driver's eye aspect ratio, the system can use the optimal threshold value to determine the driver's condition. In addition, the system synthesizes an input image from the gray-scaled and LAB model images to operate in low lighting conditions.

Contour-based Procedural Modeling of Leaf Venation Patterns (컨투어기반 잎맥 패턴의 절차적 모델링)

  • Kim, Jin-Mo
    • Journal of Korea Game Society
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    • v.14 no.5
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    • pp.97-106
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    • 2014
  • This study proposes an efficient method to model various and diverse leaves required to express digital plants such as flowers and trees in virtual landscape easily and intuitively. The proposed procedural method divides a leaf mainly into a blade and vein thereby detecting contours from binary images that correspond to blades and generating leaves by modeling leaf veins procedurally based on the detected contours. First of all, a complicated leaf vein structure is divided into main veins, lateral veins, and tertiary vein while all veins grow procedurally directing from start auxin to destination auxin. Here, to calculate destination auxin required for growth automatically, approximated contours from binary images that correspond to blades are found thereby calculating candidate destination auxin. Finally, natural digital leaves are generated by applying a color combination method. Through the proposed method, natural and various leaves can be generated and whether the proposed method is efficient or not is verified through the experiment.

Fault Detection Sensitivity of a Data-driven Empirical Model for the Nuclear Power Plant Instruments (데이터 기반 경험적 모델의 원전 계측기 고장검출 민감도 평가)

  • Hur, Seop;Kim, Jae-Hwan;Kim, Jung-Taek;Oh, In-Sock;Park, Jae-Chang;Kim, Chang-Hwoi
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.5
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    • pp.836-842
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    • 2016
  • When an accident occurs in the nuclear power plant, the faulted information might mislead to the high possibility of aggravating the accident. At the Fukushima accident, the operators misunderstood that there was no core exposure despite in the processing of core damage, because the instrument information of the reactor water level was provided to the operators optimistically other than the actual situation. Thus, this misunderstanding actually caused to much confusions on the rapid countermeasure on the accident, and then resulted in multiplying the accident propagation. It is necessary to be equipped with the function that informs operators the status of instrument integrity in real time. If plant operators verify that the instruments are working properly during accident conditions, they are able to make a decision more safely. In this study, we have performed various tests for the fault detection sensitivity of an data-driven empirical model to review the usability of the model in the accident conditions. The test was performed by using simulation data from the compact nuclear simulator that is numerically simulated to PWR type nuclear power plant. As a result of the test, the proposed model has shown good performance for detecting the specified instrument faults during normal plant conditions. Although the instrument fault detection sensitivity during plant accident conditions is lower than that during normal condition, the data-drive empirical model can be detected an instrument fault during early stage of plant accidents.

Study on Face recognition algorithm using the eye detection (눈 검출을 이용한 얼굴인식 알고리즘에 관한 연구)

  • Park, Byung-Joon;Kim, Ki-young;Kim, Sun-jib
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.8 no.6
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    • pp.491-496
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    • 2015
  • Cloud computing has emerged with promise to decrease the cost of server additional cost and expanding the data storage and ease for computer resource sharing and apply the new technologies. However, Cloud computing also raises many new security concerns due to the new structure of the cloud service models. Therefore, the secure user authentication is required when the user is using cloud computing. This paper, we propose the enhanced AdaBoost algorithm for access cloud security zone. The AdaBoost algorithm despite the disadvantage of not detect a face inclined at least 20, is widely used because of speed and responsibility. In the experimental results confirm that a face inclined at least 20 degrees tilted face was recognized. Using the FEI Face Database that can be used in research to obtain a result of 98% success rate of the algorithm perform. The 2% failed rate is due to eye detection error which is the people wearing glasses in the picture.

Hand Feature Extraction Algorithm Using Curvature Analysis For Recognition of Various Hand Gestures (다양한 손 제스처 인식을 위한 곡률 분석 기반의 손 특징 추출 알고리즘)

  • Yoon, Hong-Chan;Cho, Jin-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.5
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    • pp.13-20
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    • 2015
  • In this paper, we propose an algorithm that can recognize not only the number of stretched fingers but also determination of attached fingers for extracting features required for hand gesture recognition. The proposed algorithm detects the hand area in the input image by the skin color range filter based on a color model and labeling, and then recognizes various hand gestures by extracting the number of stretched fingers and determination of attached fingers using curvature information extracted from outlines and feature points. Experiment results show that the recognition rate and the frame rate are similar to those of the conventional algorithm, but the number of gesture cases that can be defined by the extracted characteristics is about four times higher than the conventional algorithm, so that the proposed algorithm can recognize more various gestures.

Long-Distance Plume Detection Simulation for a New MWIR Camera (장거리 화염 탐지용 적외선 카메라 성능 광선추적 수치모사)

  • Yoon, Jeeyeon;Ryu, Dongok;Kim, Sangmin;Seong, Sehyun;Yoon, Woongsup;Kim, Jieun;Kim, Sug-Whan
    • Korean Journal of Optics and Photonics
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    • v.25 no.5
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    • pp.245-253
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    • 2014
  • We report a realistic field-performance simulation for a new MWIR camera. It is designed for early detection of missile plumes over a distance range of a few hundred kilometers. Both imaging and radiometric performance of the camera are studied by using real-scale integrated ray tracing, including targets, atmosphere, and background scene models. The simulation results demonstrate that the camera would satisfy the imaging and radiometric performance requirements for field operation.

A Study on Basalization of the Classification in Mountain Ginseng and Plain Ginseng Images in Artificial Intelligence Technology for the Detection of Illegal Mountain Ginseng (불법 산양삼 검출을 위한 인공지능 기술에서의 산양삼과 인삼 이미지의 분류 기저화 연구)

  • Park, Soo-Kyoung;Na, Hojun;Kim, Ji-Hye
    • The Journal of Bigdata
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    • v.5 no.1
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    • pp.209-225
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    • 2020
  • This study tried to establish a base level for the form of ginseng in order to prevent fraud in which novice consumers, who have no information on ginseng and mountain ginseng, regard ginseng as mountain ginseng. To that end, researchers designed a service design in which when a consumer takes a picture of ginseng with an APP dedicated to a smartphone, the photo is sent remotely and the determined results are sent to the consumer based on machine learning data. In order to minimize the difference between the data set in the research process and the background color, location, size, illumination, and color temperature of the mountain ginseng when consumers took pictures through their smartphones, the filming box exclusively for consumers was designed. Accordingly, the collection of mountain ginseng samples was made under the same controlled environment and setting as the designed box. This resulted in a 100% predicted probability from the CNN(VGG16) model using a sample that was about one-tenth less than widley required in machine learning.