• Title/Summary/Keyword: 잡음 제거 필터

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Development of GPS data recovery circuit using CPSO (CPSO를 이용한 GPS위성 데이터 추출회로 개발)

  • 변건식;정명덕;박지언;최희주;김성곤
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.2 no.3
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    • pp.317-323
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    • 1998
  • A synchronization is important element not only wire communication but also wireless communication. Especially, In SS(Spread Spectrum) communication method used GPS(Global Positioning System) synchronization is more important. A synchronous oscillator(SO) is a network which synchronizes, tracks, filter, amplifies and divides (if necessary) in a single process. Without an input signal, the SO is a free-running oscillator, oscillating at a frequency $w_0$, but phase changes $180^{\circ}$ within tracking range of SO. Therefore CPSO was used for this problem. The coherent phase synchronous oscillator(CPSO) is created by adding two external loops to the SO and has a wider tracking bandwidth and a zero-offset phase response (coherent) while maintaining the SO properties of high signal-to-rejection and fast frequency acquisition times. Therefore phase between input signal and output signal is synchronized. In this paper, GPS data recovery circuit has applied CPSO using front reference characters and has certified an excellent data recovery capability.

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A Vehicle License Plate Recognition Using the Haar-like Feature and CLNF Algorithm (Haar-like Feature 및 CLNF 알고리즘을 이용한 차량 번호판 인식)

  • Park, SeungHyun;Cho, Seongwon
    • Smart Media Journal
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    • v.5 no.1
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    • pp.15-23
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    • 2016
  • This paper proposes an effective algorithm of Korean license plate recognition. By applying Haar-like feature and Canny edge detection on a captured vehicle image, it is possible to find a connected rectangular, which is a strong candidate for license plate. The color information of license plate separates plates into white and green. Then, OTSU binary image processing and foreground neighbor pixel propagation algorithm CLNF will be applied to each license plates to reduce noise except numbers and letters. Finally, through labeling, numbers and letters will be extracted from the license plate. Letter and number regions, separated from the plate, pass through mesh method and thinning process for extracting feature vectors by X-Y projection method. The extracted feature vectors are classified using neural networks trained by backpropagation algorithm to execute final recognition process. The experiment results show that the proposed license plate recognition algorithm works effectively.

Recognition of Resident Registration Cards Using ART-1 and PCA Algorithm (ART-1과 PCA 알고리즘을 이용한 주민등록증 인식)

  • Park, Sung-Dae;Woo, Young-Woon;Kim, Kwang-Baek
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.9
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    • pp.1786-1792
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    • 2007
  • In this paper, we proposed a recognition system for resident registration cards using ART-1 and PCA algorithm. To extract registration numbers and issue date, Sobel mask and median filter are applied first and noise removal follows. From the noise-removed image, horizontal smearing is used to extract the regions, which are binarized with recursive binarization algorithm. After that vortical smearing is applied to restore corrupted lesions, which are mainly due to the horizontal smearing. from the restored image, areas of individual codes are extracted using 4-directional edge following algorithm and face area is extracted by the morphologic characteristics of a registration card. Extracted codes are recognized using ART-1 algorithm and PCA algorithm is used to verify the face. When the proposed method was applied to 25 real registration card images, 323 characters from 325 registration numbers and 166 characters from 167 issue date numbers, were correctly recognized. The verification test with 25 forged images showed that the proposed verification algorithm is robust to detect forgery.

Building Roof Reconstruction in Remote Sensing Image using Line Segment Extraction and Grouping (선소의 추출과 그룹화를 이용한 원격탐사영상에서 건물 지붕의 복원)

  • 예철수;전승헌;이호영;이쾌희
    • Korean Journal of Remote Sensing
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    • v.19 no.2
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    • pp.159-169
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    • 2003
  • This paper presents a method for automatic 3-d building reconstruction using high resolution aerial imagery. First, by using edge preserving filtering, noise is eliminated and then images are segmented by watershed algorithm, which preserves location of edge pixels. To extract line segments between control points from boundary of each region, we calculate curvature of each pixel on the boundary and then find the control points. Line segment linking is performed according to direction and length of line segments and the location of line segments is adjusted using gradient magnitudes of all pixels of the line segment. Coplanar grouping and pplygonal patch formation are performed per region by selecting 3-d line segments that are matched using epipolar geometry and flight information. The algorithm has been applied to high resolution aerial images and the results show accurate 3D building reconstruction.

Optimal Design Space Exploration of Multi-core Architecture for Real-time Lane Detection Algorithm (실시간 차선인식 알고리즘을 위한 최적의 멀티코어 아키텍처 디자인 공간 탐색)

  • Jeong, Inkyu;Kim, Jongmyon
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.3
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    • pp.339-349
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    • 2017
  • This paper proposes a four-stage algorithm for detecting lanes on a driving car. In the first stage, it extracts region of interests in an image. In the second stage, it employs a median filter to remove noise. In the third stage, a binary algorithm is used to classify two classes of backgrond and foreground of an input image. Finally, an image erosion algorithm is utilized to obtain clear lanes by removing noises and edges remained after the binary process. However, the proposed lane detection algorithm requires high computational time. To address this issue, this paper presents a parallel implementation of a real-time line detection algorithm on a multi-core architecture. In addition, we implement and simulate 8 different processing element (PE) architectures to select an optimal PE architecture for the target application. Experimental results indicate that 40×40 PE architecture show the best performance, energy efficiency and area efficiency.

Transmission of 200-Gb/s 2-channel OTDM-PAM4 Signal Based on CSRZ Pulse Generated by Mach-Zehnder Modulator (마하 젠더 변조기로 생성된 CSRZ 펄스 기반의 200 Gb/s OTDM-PAM4 신호의 전송)

  • Sunghyun Bae
    • Korean Journal of Optics and Photonics
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    • v.34 no.4
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    • pp.151-156
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    • 2023
  • We propose to implement cost-effectively a high-speed short-haul interconnect by transmitting a 200-Gb/s/λ two-channel optical time-division-multiplexed signal generated by a carrier-suppressed optical pulse, which improves the robustness of the multiplexed signal to chromatic dispersion. The multiplexed 200-Gb/s signal is generated in the transmitter by combining two 100-Gb/s 4-level pulse-amplitude-modulated signals (generated using the optical pulse and two Mach-Zehnder modulators). After the signal is transmitted over a fiber, it is amplified by a semiconductor optical amplifier and detected by a photodiode. The amplified spontaneous emission noise is eliminated by an optical band-pass filter. The transmitted signal is reconstructed by a 2 × 2 multiple-input multiple-output equalizer, which compensates for crosstalk. Due to the use of the carrier-suppressed optical pulse, the 200-Gb/s signal can be transmitted over fiber with a chromatic dispersion of 40 ps/nm.

Pace and Facial Element Extraction in CCD-Camera Images by using Snake Algorithm (스네이크 알고리즘에 의한 CCD 카메라 영상에서의 얼굴 및 얼굴 요소 추출)

  • 판데홍;김영원;김정연;전병환
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2002.11a
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    • pp.535-542
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    • 2002
  • 최근 IT 산업이 급성장하면서 화상 회의, 게임, 채팅 등에서의 아바타(avatar) 제어를 위한 자연스러운 인터페이스 기술이 요구되고 있다. 본 논문에서는 동적 윤곽선 모델(active contour models; snakes)을 이용하여 복잡한 배경이 있는 컬러 CCD 카메라 영상에서 얼굴과 눈, 입, 눈썹, 코 등의 얼굴 요소에 대해 윤곽선을 추출하거나 위치를 파악하는 방법을 제안한다. 일반적으로 스네이크 알고리즘은 잡음에 민감하고 초기 모델을 어떻게 설정하는가에 따라 추출 성능이 크게 좌우되기 때문에 주로 단순한 배경의 영상에서 정면 얼굴의 추출에 사용되어왔다 본 연구에서는 이러한 단점을 파악하기 위해, 먼저 YIQ 색상 모델의 I 성분을 이용한 색상 정보와 차 영상 정보를 사용하여 얼굴의 최소 포함 사각형(minimum enclosing rectangle; MER)을 찾고, 이 얼굴 영역 내에서 기하학적인 위치 정보와 에지 정보를 이용하여 눈, 입, 눈썹, 코의 MER을 설정한다. 그런 다음, 각 요소의 MER 내에서 1차 미분과 2차 미분에 근거한 내부 에너지와 에지에 기반한 영상 에너지를 이용한 스네이크 알고리즘을 적용한다. 이때, 에지 영상에서 얼굴 주변의 복잡한 잡음을 제거하기 위하여 색상 정보 영상과 차 영상에 각각 모폴로지(morphology)의 팽창(dilation) 연산을 적용하고 이들의 AND 결합 영상에 팽창 연산을 다시 적용한 이진 영상을 필터로 사용한다. 총 7명으로부터 양 눈이 보이는 정면 유사 방향의 영상을 20장씩 취득하여 총 140장에 대해 실험한 결과, MER의 오차율은 얼굴, 눈, 입에 대해 각각 6.2%, 11.2%, 9.4%로 나타났다. 또한, 스네이크의 초기 제어점을 얼굴은 44개, 눈은 16개, 입은 24개로 지정하여 MER추출에 성공한 영상에 대해 스네이크 알고리즘을 수행한 결과, 추출된 영역의 오차율은 각각 2.2%, 2.6%, 2.5%로 나타났다.해서 Template-based reasoning 예를 보인다 본 방법론은 검색노력을 줄이고, 검색에 있어 Feasibility와 Admissibility를 보장한다.매김할 수 있는 중요한 계기가 될 것이다.재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.ting LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity of computation. Adaptive transversal filter with proposed data recycling buffer algorithm could efficiently reject ISI of channel and increase speed of convergence in avoidance burden of computational complexity in reality when it was experimented having the same condition of

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Co-registration of PET-CT Brain Images using a Gaussian Weighted Distance Map (가우시안 가중치 거리지도를 이용한 PET-CT 뇌 영상정합)

  • Lee, Ho;Hong, Helen;Shin, Yeong-Gil
    • Journal of KIISE:Software and Applications
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    • v.32 no.7
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    • pp.612-624
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    • 2005
  • In this paper, we propose a surface-based registration using a gaussian weighted distance map for PET-CT brain image fusion. Our method is composed of three main steps: the extraction of feature points, the generation of gaussian weighted distance map, and the measure of similarities based on weight. First, we segment head using the inverse region growing and remove noise segmented with head using region growing-based labeling in PET and CT images, respectively. And then, we extract the feature points of the head using sharpening filter. Second, a gaussian weighted distance map is generated from the feature points in CT images. Thus it leads feature points to robustly converge on the optimal location in a large geometrical displacement. Third, weight-based cross-correlation searches for the optimal location using a gaussian weighted distance map of CT images corresponding to the feature points extracted from PET images. In our experiment, we generate software phantom dataset for evaluating accuracy and robustness of our method, and use clinical dataset for computation time and visual inspection. The accuracy test is performed by evaluating root-mean-square-error using arbitrary transformed software phantom dataset. The robustness test is evaluated whether weight-based cross-correlation achieves maximum at optimal location in software phantom dataset with a large geometrical displacement and noise. Experimental results showed that our method gives more accuracy and robust convergence than the conventional surface-based registration.

Driver's Status Recognition Using Multiple Wearable Sensors (다중 웨어러블 센서를 활용한 운전자 상태 인식)

  • Shin, Euiseob;Kim, Myong-Guk;Lee, Changook;Kang, Hang-Bong
    • KIPS Transactions on Computer and Communication Systems
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    • v.6 no.6
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    • pp.271-280
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    • 2017
  • In this paper, we propose a new safety system composed of wearable devices, driver's seat belt, and integrating controllers. The wearable device and driver's seat belt capture driver's biological information, while the integrating controller analyzes captured signal to alarm the driver or directly control the car appropriately according to the status of the driver. Previous studies regarding driver's safety from driver's seat, steering wheel, or facial camera to capture driver's physiological signal and facial information had difficulties in gathering accurate and continuous signals because the sensors required the upright posture of the driver. Utilizing wearable sensors, however, our proposed system can obtain continuous and highly accurate signals compared to the previous researches. Our advanced wearable apparatus features a sensor that measures the heart rate, skin conductivity, and skin temperature and applies filters to eliminate the noise generated by the automobile. Moreover, the acceleration sensor and the gyro sensor in our wearable device enable the reduction of the measurement errors. Based on the collected bio-signals, the criteria for identifying the driver's condition were presented. The accredited certification body has verified that the devices has the accuracy of the level of medical care. The laboratory test and the real automobile test demonstrate that our proposed system is good for the measurement of the driver's condition.

Recovery of Lithospheric Magnetic Component in the Satellite Magnetometer Observations of East Asia (인공위성 자력계에서 관측된 동아시아 암권의 지자기이상)

  • Kim, Jeong-Woo
    • Geophysics and Geophysical Exploration
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    • v.5 no.3
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    • pp.157-168
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    • 2002
  • Improved procedures were implemented in the production of the lithospheric magnetic anomaly map from Magsat satellite magnetometer data of East Asia between $90^{\circ}E-150^{\circ}E$ and $10^{\circ}S-50^{\circ}N$. Procedures included more effective selection of the do·it and dawn tracks, ring current correction, and separation of core field and external field effects. External field reductions included an ionospheric correction and pass-by-pass correlation analysis. Track-line noise effects were reduced by spectral reconstruction of the dusk and dawn data sets. The total field magnetic anomalies were differentially-reduced-to-the-pole to minimize distortion s between satellite magnetic anomalies and their geological sources caused by corefield variations over the study area. Aeromagnetic anomalies were correlated with Magsat magnetic anomalies at the satellite altitude to test the lithospheric veracity of anomalies in these two data sets. The aeromagnetic anomalies were low-pass filtered to eliminate high frequency components that may not be shown at the satellite altitude. Although the two maps have a low CC of 0.243, there are many features that are directly correlated (peak-to-peak and trough-to-trough). The low CC between the two maps was generated by the combination of directly- and inversely-correlative anomaly features between them. It is very difficult to discriminate directly, inversely, and nully correlative features in these two anomaly maps because features are complicatedly correlated due to the depth and superposition of the anomaly sources. In general, the lithospheric magnetic components were recovered successfully from satellite magnetometer observations and correlated well with aeromagnetic anomalies in the study area.