• Title/Summary/Keyword: shift algorithm

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Clothing Color Analysis Techniques using Bilateral Filter and Mean-Shift Algorithm (Bilateral 필터와 Mean-Shift 알고리즘을 이용한 의상 색상 분석기법)

  • Kim, Hye-Min;Jeong, Chang-Seong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2015.10a
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    • pp.1413-1415
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    • 2015
  • 본 논문에서 우리는 의상영역의 유사성을 검사 시 색상분석에 있어 정확도를 향상시키기 위해 Bilateral 필터와 Mean-Shift 알고리즘을 적용하였다. 본 연구의 평가부분에서 필터를 적용한 영상이 의상영역의 구김이나 빛에 의한 영향이 필터를 적용하지 않은 영상보다 적다는 것을 실험을 통해 증명한다.

FPGA Implementation of Unitary MUSIC Algorithm for DoA Estimation (도래방향 추정을 위한 유니터리 MUSIC 알고리즘의 FPGA 구현)

  • Ju, Woo-Yong;Lee, Kyoung-Sun;Jeong, Bong-Sik
    • Journal of the Institute of Convergence Signal Processing
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    • v.11 no.1
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    • pp.41-46
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    • 2010
  • In this paper, the DoA(Direction of Arrival) estimator using unitary MUSIC algorithm is studied. The complex-valued correlation matrix of MUSIC algorithm is transformed to the real-valued one using unitary transform for easy implementation. The eigenvalue and eigenvector are obtained by the combined Jacobi-CORDIC algorithm. CORDIC algorithm can be implemented by only ADD and SHIFT operations and MUSIC spectrum computed by 256 point DFT algorithm. Results of unitary MUSIC algorithm designed by System Generator for FPGA implementation is entirely consistent with Matlab results. Its performance is evaluated through hardware co-simulation and resource estimation.

An Improvement on FFT-Based Digital Implementation Algorithm for MC-CDMA Systems (MC-CDMA 시스템을 위한 FFT 기반의 디지털 구현 알고리즘 개선)

  • 김만제;나성주;신요안
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.7A
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    • pp.1005-1015
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    • 1999
  • This paper is concerned with an improvement on IFFT (inverse fast Fourier transform) and FFT based baseband digital implementation algorithm for BPSK (binary phase shift keying)-modulated MC-CDMA (multicarrier-code division multiple access) systems, that is functionally equivalent to the conventional implementation algorithm, while reducing computational complexity and bandwidth requirement. We also derive an equalizer structure for the proposed implementation algorithm. The proposed algorithm is based on a variant of FFT algorithm that utilizes a N/2-point FFT/IFFT for simultaneous transformation and reconstruction of two N/2-point real signals. The computer simulations under additive white Gaussian noise channels and frequency selective fading channels using equal gain combiner and maximal ratio combiner diversities, demonstrate the performance of the proposed algorithm.

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Adaptive Compensation Method Using the Prediction Algorithm for the Doppler Frequency Shift in the LEO Mobile Satellite Communication System

  • You, Moon-Hee;Lee, Seong-Pal;Han, Young-Yearl
    • ETRI Journal
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    • v.22 no.4
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    • pp.32-39
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    • 2000
  • In low earth orbit (LEO) satellite communication systems, more severe phase distortion due to Doppler shift is frequently detected in the received signal than in cases of geostationary earth orbit (GEO) satellite systems or terrestrial mobile systems. Therefore, an estimation of Doppler shift would be one of the most important factors to enhance performance of LEO satellite communication system. In this paper, a new adaptive Doppler compensation scheme using location information of a user terminal and satellite, as well as a weighting factor for the reduction of prediction error is proposed. The prediction performance of the proposed scheme is simulated in terms of the prediction accuracy and the cumulative density function of the prediction error, with considering the offset variation range of the initial input parameters in LEO satellite system. The simulation results showed that the proposed adaptive compensation algorithm has the better performance accuracy than Ali's method. From the simulation results, it is concluded the adaptive compensation algorithm is the most applicable method that can be applied to LEO satellite systems of a range of altitude between 1,000 km and 2,000 km for the general error tolerance level, M = 250 Hz.

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A 3-cell CCI(Cell-to-Cell Interference) model and error correction algorithm for Multi-level cell NAND Flash Memories (다중셀 낸드 플래시 메모리의 3셀 CCI 모델과 이를 이용한 에러 정정 알고리듬)

  • Jung, Jin-Ho;Kim, Shi-Ho
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.48 no.10
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    • pp.25-32
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    • 2011
  • We have analyzed adjacent cell dependency of threshold voltage shift caused by the cell to cell interference, and we proposed a 3-adjacent-cell model to model the pattern dependency of the threshold voltage shift. The proposed algorithm is verified by using MATLAB simulation and measurement results. In the experimental results, we found that accuracy of the proposed simple 3-adjacient-cell model is comparable to the widely used conventional 8-adjacient-cell model. The Bit Error Rate (BER) of LSB and of MSB is improved by 28.9% and 19.8%, respectively, by applying the proposed algorithm based on 3-adjacent-cell model to 20nm-class 2-bit MLC NAND flash memories.

Design of a Recognizing System for Vehicle's License Plates with English Characters

  • Xing, Xiong;Choi, Byung-Jae;Chae, Seog;Lee, Mun-Hee
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.9 no.3
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    • pp.166-171
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    • 2009
  • In recent years, video detection systems have been implemented in various infrastructures such as airport, public transportation, power generation system, water dam and so on. Recognizing moving objects in video sequence is an important problem in computer vision, with applications in several fields, such as video surveillance and target tracking. Segmentation and tracking of multiple vehicles in crowded situations is made difficult by inter-object occlusion. In the system described in this paper, the mean shift algorithm is firstly used to filter and segment a color vehicle image in order to get candidate regions. These candidate regions are then analyzed and classified in order to decide whether a candidate region contains a license plate or not. And then some characters in the license plate is recognized by using the fuzzy ARTMAP neural network, which is a relatively new architecture of the neural network family and has the capability to learn incrementally unlike the conventional BP network. We finally design a license plate recognition system using the mean shift algorithm and fuzzy ARTMAP neural network and show its performance via some computer simulations.

Movement Detection Algorithm Using Virtual Skeleton Model (가상 모델을 이용한 움직임 추출 알고리즘)

  • Joo, Young-Hoon;Kim, Se-Jin
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.6
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    • pp.731-736
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    • 2008
  • In this paper, we propose the movement detection algorithm by using virtual skeleton model. To do this, first, we eliminate error values by using conventioanl method based on RGB color model and eliminate unnecessary values by using the HSI color model. Second, we construct the virtual skeleton model with skeleton information of 10 peoples. After matching this virtual model to original image, we extract the real head silhouette by using the proposed circle searching method. Third, we extract the object by using the mean-shift algorithm and this head information. Finally, we validate the applicability of the proposed method through the various experiments in a complex environments.

Implementation of an improved real-time object tracking algorithm using brightness feature information and color information of object

  • Kim, Hyung-Hoon;Cho, Jeong-Ran
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.5
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    • pp.21-28
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    • 2017
  • As technology related to digital imaging equipment is developed and generalized, digital imaging system is used for various purposes in fields of society. The object tracking technology from digital image data in real time is one of the core technologies required in various fields such as security system and robot system. Among the existing object tracking technologies, cam shift technology is a technique of tracking an object using color information of an object. Recently, digital image data using infrared camera functions are widely used due to various demands of digital image equipment. However, the existing cam shift method can not track objects in image data without color information. Our proposed tracking algorithm tracks the object by analyzing the color if valid color information exists in the digital image data, otherwise it generates the lightness feature information and tracks the object through it. The brightness feature information is generated from the ratio information of the width and the height of the area divided by the brightness. Experimental results shows that our tracking algorithm can track objects in real time not only in general image data including color information but also in image data captured by an infrared camera.

Optimal Radar Pulse Compression Processing Algorithm and the Resulting Optimal Codes for Pulse Compressed Signals (레이더 펄스 압축 신호의 최적 탐색 알고리즘 개발 및 최적 코드에 관한 연구)

  • 김효준;이명수;김영기;송문호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.6B
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    • pp.1100-1105
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    • 2000
  • The most widely used radar pulse compression technique is correlation processing using Barker code. This technique enhances detection sensitivity but, unfortunately, suffers from the addition of range sidelobes which sometimes will degrade the performance of radar systems. In this paper, our proposed optimal algorithm eliminates the sidelobes at the cost of additional processing and is evaluated in the presence of Doppler shift. We then propose optimal codes with regard to the proposed algorithm and the performance is compared against the traditional correlation processing with Barker codes. The proposed processing using optimal codes will be shown to be superior over the traditional processing in the presence of Doppler shift.

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Inforamtion Application for The blind people (시각 장애인을 위한 안내정보 어플리케이션)

  • Shin, Eun-bi;Roh, Tae-Kyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.358-359
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    • 2018
  • In this paper, opencv and android studio are used to distinguish between objects ahead of the blind. When the movement is detected in a positive direction in connection with the camera of the smartphone, the user is informed that the part of the camera is being rabelified and continues to track using the mean shift algorithm. A C ++ program based on OpenCV-based was used for real-time motion observation and the application will be produced by android studio. As a result of the study, objects that move with Labeling are identified and the box area is specified using the mean shift algorithm to move the box along with the object to track objects in real time.

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