• Title/Summary/Keyword: distance transform

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A Study on the Change in the Film Thickness of Ball Bearing in Starved EHL (윤활유 부족 상태에서의 볼 베어링 유막 두께 변화에 대한 연구)

  • Jung, SoonBi;Lee, Bora;Yu, YongHun;Cho, YongJoo
    • Tribology and Lubricants
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    • v.33 no.3
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    • pp.119-125
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    • 2017
  • In this study, we perform a numerical analysis to predict the film thickness and lubrication regions for a thrust ball bearing under different operating conditions. Film thinning and replenishment affect the film thickness in starved lubrication. As the inlet meniscus position is brought to the edge of the Hertz contact, the thin film thickness is calculated as starved equation. We use a film replenishment model to determine the recovery film thickness between rolling elements. We use a hydrodynamic model to describe film recovery, that results from the effects of surface tension. In this model, we consider the surface tension gradient in fluid depression as the driving force for fluid recovery. We use Fourier transform method to determine the time-dependent depth of depressed oil. We calculate the change in the central film thickness graphically by using the recovery equation in starved elastohydrodynamic lubrication(EHL) under operating conditions that include numbers of balls, sliding velocity, applied force, and ambient film thickness. We evaluate the degree of starvation by using the distance from the center of the contact area to the meniscus position. Parched lubrication, a phenomenon where the film thickness decreases consistently, occurs at the severe condition. We determine optimal values with respect to the numbers of balls, and sliding velocity. The investigation can contribute to the design operating conditions for proper lubrication.

Geometrical Reorientation of Distorted Road Sign using Projection Transformation for Road Sign Recognition (도로표지판 인식을 위한 사영 변환을 이용한 왜곡된 표지판의 기하교정)

  • Lim, Hee-Chul;Deb, Kaushik;Jo, Kang-Hyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.11
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    • pp.1088-1095
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    • 2009
  • In this paper, we describe the reorientation method of distorted road sign by using projection transformation for improving recognition rate of road sign. RSR (Road Sign Recognition) is one of the most important topics for implementing driver assistance in intelligent transportation systems using pattern recognition and vision technology. The RS (Road Sign) includes direction of road or place name, and intersection for obtaining the road information. We acquire input images from mounted camera on vehicle. However, the road signs are often appeared with rotation, skew, and distortion by perspective camera. In order to obtain the correct road sign overcoming these problems, projection transformation is used to transform from 4 points of image coordinate to 4 points of world coordinate. The 4 vertices points are obtained using the trajectory as the distance from the mass center to the boundary of the object. Then, the candidate areas of road sign are transformed from distorted image by using homography transformation matrix. Internal information of reoriented road signs is segmented with arrow and the corresponding indicated place name. Arrow area is the largest labeled one. Also, the number of group of place names equals to that of arrow heads. Characters of the road sign are segmented by using vertical and horizontal histograms, and each character is recognized by using SAD (Sum of Absolute Difference). From the experiments, the proposed method has shown the higher recognition results than the image without reorientation.

Detecting Line Segment by Incremental Pixel Extension (점진적인 화소 확장에 의한 선분 추출)

  • Lee, Jae-Kwang;Park, Chang-Joon
    • Journal of Korea Multimedia Society
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    • v.11 no.3
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    • pp.292-300
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    • 2008
  • An algorithm for detecting a line segment in an image is presented using incremental pixel extension. We use a different approach from conventional algorithms, such as the Hough transform approach and the line segment grouping approach. The Canny edge is calculated and an arbitrary point is selected among the edge elements. After the arbitrary point is selected, a base line approximating the line segment is calculated and edge pixels within an arbitrary radius are selected. A weighted value is assigned to each edge pixel, which is selected by using the error of the distance and the direction between the pixel and the base line. A line segment is extracted by Jilting a line using the weighted least square method after determining whether selected pixels are linked or delinked using the sum comparison of the weights. The proposed algorithm is compared with two other methods and results show that our algorithm is faster and can detect the real line segment.

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3-D Object Tracking using 3-D Information and Optical Correlator in the Stereo Vision System (스테레오 비젼 시스템에서 3차원정보와 광 상관기를 이용한 3차원 물체추적 방법)

  • 서춘원;이승현;김은수
    • Journal of Broadcast Engineering
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    • v.7 no.3
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    • pp.248-261
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    • 2002
  • In this paper, we proposed a new 3-dimensional(3-D) object-tracking algorithm that can control a stereo camera using a variable window mask supported by which uses ,B-D information and an optical BPEJTC. Hence, three-dimensional information characteristics of a stereo vision system, distance information from the stereo camera to the tracking object. can be easily acquired through the elements of a stereo vision system. and with this information, we can extract an area of the tracking object by varying window masks. This extractive area of the tracking object is used as the next updated reference image. furthermore, by carrying out an optical BPEJTC between a reference image and a stereo input image the coordinates of the tracking objects location can be acquired, and with this value a 3-D object tracking can be accomplished through manipulation of the convergence angie and a pan/tilt of a stereo camera. From the experimental results, the proposed algorithm was found to be able to the execute 3-D object tracking by extracting the area of the target object from an input image that is independent of the background noise in the stereo input image. Moreover a possible implementation of a 3-D tele-working or an adaptive 3-D object tracker, using the proposed algorithm is suggested.

Discrimination of Local Microearthquakes and Artificial Underground Explosions on the Basis of Time-Frequency Domain (시간-주파수 영역에서의 국지 미소지진과 지하인공폭발의 구별)

  • 김소구;박용철
    • The Journal of Engineering Geology
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    • v.7 no.1
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    • pp.63-79
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    • 1997
  • In this study, our purpose is to develop a technique to discriminate artificial explosions from local microearthquakes on the basis of time-frequency domain. To obtain spectral features of artificial explosions and microearthquakes, we used 3-d spectrograms(frequency, time and amplitude) because this is a useful tool to study the frequency content of entire seismic waveforms observed at local and regional distances (e. g., Kim et al., 1994). P and S waves from quarry blasts show that frequency content of dominant amplitude appeared above 10 Hz and Rg phases that are observed at near distance ranges. But P and S waves from microearthquakes have more broad frequency content as well as below 10 Hz. And for discrimination, Pg/Lg spectral ratio is performed below 10 Hz. In order to select time windows we computed group velocity using multiple filter method(MFM) and removed free surface effects from all 3-components data for improving on data quality. Next step, we computed Fast-Fourier transform, and a log average spectral amplitude over seven frequency bands : 0.5 to 3, 2 to 4, 3 to 5, 4 to 6, 5 to 7, 6 to 8 and 8 to 10 Hz. The best separation is observed from 6 to 8 Hz.

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Iris Detection at a Distance by Non-volunteer Method (비강압적 방법에 의한 원거리에서의 홍채 탐지 기법)

  • Park, Kwon-Do;Kim, Dong-Su;Kim, Jeong-Min;Song, Young-Ju;Koh, Seok-Joo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.705-708
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    • 2018
  • Among biometrics commercialized for security, iris recognition technology has the most excellent security for the probability of the match between individuals is the lowest. Current commercialized iris recognition technology has excellent recognition ability, but this technology has a fatal drawback. Without the user's active cooperation, it cannot recognize the iris correctly. To make up for this weakness, recent trend of iris recognition development mounts a non-volunteering, unconstrained method. According to this information, the objective of this research is developing a module that can identify people iris from a video acquired by high performance infrared camera in a range of 3m and in a involuntary way. For this, we import images from the video and find people's face and eye positions from the images using Haar classifier trained through Cascade training method. finally, we crop the iris by Hough circle transform and compare it with data from the database to identify people.

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A study on Iris Recognition using Wavelet Transformation and Nonlinear Function

  • Hur, Jung-Youn;Truong, Le Xuan
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.10a
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    • pp.553-559
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    • 2004
  • In todays security industry, personal identification is also based on biometric. Biometric identification is performed basing on the measurement and comparison of physiological and behavioral characteristics, Biometric for recognition includes voice dynamics, signature dynamics, hand geometry, fingerprint, iris, etc. Iris can serve as a kind of living passport or living password. Iris recognition system is the one of the most reliable biometrics recognition system. This is applied to client/server system such as the electronic commerce and electronic banking from stand-alone system or networks, ATMs, etc. A new algorithm using nonlinear function in recognition process is proposed in this paper. An algorithm is proposed to determine the localized iris from the iris image received from iris input camera in client. For the first step, the algorithm determines the center of pupil. For the second step, the algorithm determines the outer boundary of the iris and the pupillary boundary. The localized iris area is transform into polar coordinates. After performing three times Wavelet transformation, normalization was done using sigmoid function. The converting binary process performs normalized value of pixel from 0 to 255 to be binary value, and then the converting binary process is compare pairs of two adjacent pixels. The binary code of the iris is transmitted to the by server. the network. In the server, the comparing process compares the binary value of presented iris to the reference value in the University database. Process of recognition or rejection is dependent on the value of Hamming Distance. After matching the binary value of presented iris with the database stored in the server, the result is transmitted to the client.

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A Secure Cluster Formation Scheme in Wireless Sensor Networks (무선 센서 네트워크에서 안전한 클러스터 구성 방안)

  • Wang, Gi-Cheol;Cho, Gi-Hwan
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.49 no.8
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    • pp.84-97
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    • 2012
  • In wireless sensor networks, cluster structure brings on many advantages such as load balancing, energy saving, and distributed key management, and so on. To transform a physical network into the cluster structure, sensor nodes should invoke a cluster formation protocol. During the protocol operation, if some nodes are compromised and they do not conform to the protocol, an inconsistency of membership in a cluster happen. This splits the cluster and consequently increases the number of clusters and decreases the number of members in the cluster. In this paper, we propose a scheme which well copes with such a problem. First, our scheme generates two hop clusters where hop distance between any two nodes is at most two. Besides, our scheme employs verification of two hop distant nodes to prevent the cluster split induced by compromised nodes. Last, our scheme mainly employs broadcast transmissions to reduce energy consumption of nodes. Simulation results have proven that our scheme reduces the number of clusters and more secure and energy-efficient than other scheme.

Radius-Measuring Algorithm for Small Tubes Based on Machine Vision using Fuzzy Searching Method (퍼지탐색을 이용한 머신비전 기반의 소형 튜브 내경측정 알고리즘)

  • Naranbaatar, Erdenesuren;Lee, Sang-Jin;Kim, Hyoung-Seok;Bae, Yong-Hwan;Lee, Byung-Ryong
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.35 no.11
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    • pp.1429-1436
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    • 2011
  • In this paper, a new tube-radius-measuring algorithm has been proposed for effectively measuring the radii of small tubes under severe noise conditions that can also perform well when metal scraps that make it difficult to measure the radius correctly are inside the tube hole. In the algorithm, we adopt a fuzzy searching method that searches for the center of the inner circle by using fuzzy parameters for distance and orientation from the initial search point. The proposed algorithm has been implemented and tested on both synthetic and real-world tube images, and the performance is compared to existing circle-detection algorithms, such as the Hough transform and RANSAC methods, to prove the accuracy and effectiveness of the algorithm. From this comparison, it is concluded that the proposed algorithm has excellent performance in terms of measurement accuracy and computation time.

Post Sender Recognition using SIFT (SIFT를 이용한 우편영상의 송신자 인식)

  • Kim, Young-Won;Jang, Seung-Ick;Lee, Sung-Jun
    • The Journal of the Korea Contents Association
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    • v.10 no.11
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    • pp.48-57
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    • 2010
  • Previous post sender recognition study was focused on recognizing the address of receiver. Relatively, there was lack of study to recognize the information of sender's address. Post sender recognition study is necessary for the service and application using sender information such as returning. This paper did the experiment and suggested how to recognize post sender using SIFT. Although SIFT shows great recognition rate, SIFT had problems with time and mis-recognition. One is increased time to match keypoints in proportion as the number of registered model. The other is mis-recognition of many similar keypoints even though they are all different models due to the nature of post sender. To solve the problem, this paper suggested SIFT adding distance function and did the experiment to compare time and function. In addition, it is suggested how to register and classify models automatically without the manual process of registering models.