• Title/Summary/Keyword: Difference of Gaussian

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THE UNIFORM CLT FOR MARTINGALE DIFFERENCE ARRAYS UNDER THE UNIFORMLY INTEGRABLE ENTROPY

  • Bae, Jong-Sig;Jun, Doo-Bae;Levental, Shlomo
    • Bulletin of the Korean Mathematical Society
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    • v.47 no.1
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    • pp.39-51
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    • 2010
  • In this paper we consider the uniform central limit theorem for a martingale-difference array of a function-indexed stochastic process under the uniformly integrable entropy condition. We prove a maximal inequality for martingale-difference arrays of process indexed by a class of measurable functions by a method as Ziegler [19] did for triangular arrays of row wise independent process. The main tools are the Freedman inequality for the martingale-difference and a sub-Gaussian inequality based on the restricted chaining. The results of present paper generalizes those of Ziegler [19] and other results of independent problems. The results also generalizes those of Bae and Choi [3] to martingale-difference array of a function-indexed stochastic process. Finally, an application to classes of functions changing with n is given.

A Study of Digital Image Analysis of Chromatin Texture for Discrimination of Thyroid Neoplastic Cells (갑상선 종양세포 식별을 위한 염색질 텍스춰의 디지탈 화상해석에 관한 연구)

  • Juhng, Sang-Woo;Lee, Jae-Hyuk;Bum, Eun-Kyung;Kim, Chang-Won
    • The Korean Journal of Cytopathology
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    • v.7 no.1
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    • pp.23-30
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    • 1996
  • Chromatin texture, which partly reflects nuclear organization, is evolving as an important parameter indicating cell activation or transformation. In this study, chromatin pattern was evaluated by image analysis of the electron micrographs of follicular and papillary carcinoma cells of the thyroid gland and tested for discrimination of the two neoplasms. Digital grey images were converted from the electron micrographs, nuclear images, excluding nucleolus and intranuclear cytoplasmic inclusions, were obtained by segmentation; grey levels were standardized; and grey level histograms were generated. The histograms in follicular carcinoma showed Gaussian or near-Gaussian distribution and had a single peak, whereas those in papillary carcinoma had two peaks(bimodal), one at the black zone and the other at the white zone. In papillary carcinoma, the peak in the black zone represented an increased amount of heterochromatin particles and that at the white zone represented decreased electron density of euchromatin or nuclear matrix. These results indicate that the nuclei of follicular and papillary carcinoma cells differ in their chromatin pattern and the difference may be due to decondensed chromatin and/or matrix substances.

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Development of a SLAM System for Small UAVs in Indoor Environments using Gaussian Processes (가우시안 프로세스를 이용한 실내 환경에서 소형무인기에 적합한 SLAM 시스템 개발)

  • Jeon, Young-San;Choi, Jongeun;Lee, Jeong Oog
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.11
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    • pp.1098-1102
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    • 2014
  • Localization of aerial vehicles and map building of flight environments are key technologies for the autonomous flight of small UAVs. In outdoor environments, an unmanned aircraft can easily use a GPS (Global Positioning System) for its localization with acceptable accuracy. However, as the GPS is not available for use in indoor environments, the development of a SLAM (Simultaneous Localization and Mapping) system that is suitable for small UAVs is therefore needed. In this paper, we suggest a vision-based SLAM system that uses vision sensors and an AHRS (Attitude Heading Reference System) sensor. Feature points in images captured from the vision sensor are obtained by using GPU (Graphics Process Unit) based SIFT (Scale-invariant Feature Transform) algorithm. Those feature points are then combined with attitude information obtained from the AHRS to estimate the position of the small UAV. Based on the location information and color distribution, a Gaussian process model is generated, which could be a map. The experimental results show that the position of a small unmanned aircraft is estimated properly and the map of the environment is constructed by using the proposed method. Finally, the reliability of the proposed method is verified by comparing the difference between the estimated values and the actual values.

Calculations of the Trapping Force of Optical Tweezers using FDTD Method (FDTD 방법을 이용한 광집게의 포획 힘 계산)

  • Sung, Seung-Yong;Lee, Yong-Gu
    • Korean Journal of Optics and Photonics
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    • v.19 no.1
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    • pp.80-83
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    • 2008
  • Optical tweezers are a tool that can use a tightly focused laser beam to trap and manipulate micron-sized dielectric particles that are immersed in a medium with lower refractive index. In this paper, the calculation of the trapping force of optical tweezers is presented. A nonparaxial Gaussian beam is used to represent a tightly focused Gaussian beam, and the FDTD (Finite-Difference Time-Domain) method is used for computing the electromagnetic field distributions in the dielectric medium. Scattered-field formulation is used for analytical expression of the incident fields. Using the electromagnetic field distribution from FDTD simulation, the trapping force is calculated based on Maxwell's stress tensor.

A Gaussian Mixture Model Based Surface Electromyogram Pattern Classification Algorithm for Estimation of Wrist Motions (손목 움직임 추정을 위한 Gaussian Mixture Model 기반 표면 근전도 패턴 분류 알고리즘)

  • Jeong, Eui-Chul;Yu, Song-Hyun;Lee, Sang-Min;Song, Young-Rok
    • Journal of Biomedical Engineering Research
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    • v.33 no.2
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    • pp.65-71
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    • 2012
  • In this paper, the Gaussian Mixture Model(GMM) which is very robust modeling for pattern classification is proposed to classify wrist motions using surface electromyograms(EMG). EMG is widely used to recognize wrist motions such as up, down, left, right, rest, and is obtained from two electrodes placed on the flexor carpi ulnaris and extensor carpi ulnaris of 15 subjects under no strain condition during wrist motions. Also, EMG-based feature is derived from extracted EMG signals in time domain for fast processing. The estimated features based in difference absolute mean value(DAMV) are used for motion classification through GMM. The performance of our approach is evaluated by recognition rates and it is found that the proposed GMM-based method yields better results than conventional schemes including k-Nearest Neighbor(k-NN), Quadratic Discriminant Analysis(QDA) and Linear Discriminant Analysis(LDA).

Study of High Speed Image Registration using BLOG (BLOG를 이용한 고속 이미지 정합에 관한 연구)

  • Kim, Jong-Min;Kang, Myung-A
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.11
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    • pp.2478-2484
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    • 2010
  • In this paper, real-time detection methods for Panorama system Key-Points offers. A recent study in PANORAMA system real-time area navigation or DVR to apply such research has recently been actively. The detection of the Key-Point is the most important elements that make up a Panorama system. Not affected by contrast, scale, Orientation must be detected Key-Point. Existing research methods are difficult to use in real-time Because it takes a lot of computation time. Therefore, this paper propose BLOG(BitRate Laplacian Of Gaussian)method for faster time Key-Point Detecting and Through various experiments to detect the Speed, Computation, detection performance is compared against.

Multiple Camera-based Person Correspondence using Color Distribution and Context Information of Human Body (색상 분포 및 인체의 상황정보를 활용한 다중카메라 기반의 사람 대응)

  • Chae, Hyun-Uk;Seo, Dong-Wook;Kang, Suk-Ju;Jo, Kang-Hyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.9
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    • pp.939-945
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    • 2009
  • In this paper, we proposed a method which corresponds people under the structured spaces with multiple cameras. The correspondence takes an important role for using multiple camera system. For solving this correspondence, the proposed method consists of three main steps. Firstly, moving objects are detected by background subtraction using a multiple background model. The temporal difference is simultaneously used to reduce a noise in the temporal change. When more than two people are detected, those detected regions are divided into each label to represent an individual person. Secondly, the detected region is segmented as features for correspondence by a criterion with the color distribution and context information of human body. The segmented region is represented as a set of blobs. Each blob is described as Gaussian probability distribution, i.e., a person model is generated from the blobs as a Gaussian Mixture Model (GMM). Finally, a GMM of each person from a camera is matched with the model of other people from different cameras by maximum likelihood. From those results, we identify a same person in different view. The experiment was performed according to three scenarios and verified the performance in qualitative and quantitative results.

Accuracy Improvement Scheme for Location Awareness based on UWB system (UWB 기반 위치인식 정확도 향상 기법)

  • Choi, Young-Hoon;Bae, Jung-Nam;Kim, Jin-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.11 no.2
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    • pp.231-236
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    • 2011
  • In recent years, LBS(Location Based Service) is applied in many different fields. Therefore, various location-aware schemes have been studied. In the location awareness system using time dependent algorithm, TOA(Time of Arrival) or TDOA(Time Difference of Arrival) algorithm, distortion of a signal by AWGN(Additive White Gaussian Noise) and multi-path effects cause the degradation of location awareness performance. In this paper, the unexpected noise is eliminated by averaging multiple pulses in order to overcome the degradation of performance. Also, we research the technique for improving the performance of the location awareness by detecting direct-path signal with adjusting threshold.

Vehicle Detection in Tunnel using Gaussian Mixture Model and Mathematical Morphological Processing (가우시안 혼합모델과 수학적 형태학 처리를 이용한 터널 내에서의 차량 검출)

  • Kim, Hyun-Tae;Lee, Geun-Hoo;Park, Jang-Sik;Yu, Yun-Sik
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.5
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    • pp.967-974
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    • 2012
  • In this paper, a vehicle detection algorithm with HD CCTV camera images using GMM(Gaussian Mixture Model) algorithm and mathematical morphological processing is proposed. At the first stage, background could be estimated using GMM from CCTV input image signal and then object could be separated from difference image of the input image and background image. At the second stage, candidated object were reformed by using mathematical morphological processing. Finally, vehicle object could be detected using vehicle size informations depend on distance and vehicle type in tunnel. Through real experiments in tunnel, it is shown that the proposed system works well.

A Detection of New Vehicle License Plates Using Difference of Gaussian and Iterative Labeling (가우시안 차이와 반복 레이블링을 이용한 신형 차량번호판 검출)

  • Yeo, Jae-yun;Kim, Min-ha;Cha, Eui-young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.10a
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    • pp.78-81
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    • 2012
  • In this paper, we proposed the new vehicle license plates detection method which is available in a various fields, including vehicle access control, illegal parking and speeding vehicle crack down. First, we binarize an image by using difference of gaussian filter to find a sequence of numbers of plates. Second, we determine the plate region by labeling repeatedly using the morphological characteristics of the plates. Finally, we use a projective transformation for correcting the distortion that occurs because of the camera or the location of the vehicle.

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