• Title/Summary/Keyword: identification rate

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An Implementation of User Identification System Using Hrbrid Biomitic Distances (복합 생체 척도 거리를 이용한 사용자 인증시스템의 구현)

  • 주동현;김두영
    • Journal of the Institute of Convergence Signal Processing
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    • v.3 no.2
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    • pp.23-29
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    • 2002
  • In this paper we proposed the user identification system using hybrid biometric information and non-contact IC card to improve the accuracy of the system. The hybrid biometric information consists of the face image, the iris image, and the 4-digit voice password of user. And the non-contact IC card provides the base information of user If the distance between the sample hybrid biometric Information corresponding to the base information of user and the measured biometric information is less than the given threshold value, the identification is accepted. Otherwise it is rejected. Through the result of experimentation, this paper shows that the proposed method has better identification rate than the conventional identification method.

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High Speed Identification Method of RFID Tag (RFID 태그의 고속 인식 기법)

  • 이광재
    • Journal of the Institute of Convergence Signal Processing
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    • v.5 no.1
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    • pp.6-12
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    • 2004
  • Identification rate and time are very important in the identification of RFID tag, and the tag requires simple structure to use economically large quantity of tags. These factors make the MAC protocols of wired or wireless network environment result in different requirements. In the paper, we propose a method to apply spread spectrum scheme using orthogonal channel via Walsh function as the anti-collision communication system for the purpose of non-collision identification of multiple tags, and consider its property. The proposed system use two step identification. in the first step, collision is resolved via constructing to respond after specific delay time based on unique n, and conventional polling scheme follows in the second step.

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MFSK Signal Individual Identification Algorithm Based on Bi-spectrum and Wavelet Analyses

  • Ye, Fang;Chen, Jie;Li, Yibing;Ge, Juan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.10
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    • pp.4808-4824
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    • 2016
  • Signal individual reconnaissance and identification is an extremely important research topic in non-cooperative domains such as electronic countermeasures and intelligence reconnaissance. Facing the characteristics of the complexity and changeability of current communication environment, how to realize radiation source signal individual identification under the low SNR conditions is an emphasis of research. A novel emitter individual identification method combined bi-spectrum analysis with wavelet feature is presented in this paper. It makes a feature fusion of bi-spectrum slice characteristics and energy variance characteristics of the secondary wavelet transform coefficient to identify MFSK signals under the low SNR (signal-to-noise ratios) environment. Theoretical analyses and computer simulation results show that the proposed algorithm has good recognition performance with the ability to suppress noise and interference, and reaches the recognition rate of more than 90% when the SNR is -6dB.

Development of Combined Architecture of Multiple Deep Convolutional Neural Networks for Improving Video Face Identification (비디오 얼굴 식별 성능개선을 위한 다중 심층합성곱신경망 결합 구조 개발)

  • Kim, Kyeong Tae;Choi, Jae Young
    • Journal of Korea Multimedia Society
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    • v.22 no.6
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    • pp.655-664
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    • 2019
  • In this paper, we propose a novel way of combining multiple deep convolutional neural network (DCNN) architectures which work well for accurate video face identification by adopting a serial combination of 3D and 2D DCNNs. The proposed method first divides an input video sequence (to be recognized) into a number of sub-video sequences. The resulting sub-video sequences are used as input to the 3D DCNN so as to obtain the class-confidence scores for a given input video sequence by considering both temporal and spatial face feature characteristics of input video sequence. The class-confidence scores obtained from corresponding sub-video sequences is combined by forming our proposed class-confidence matrix. The resulting class-confidence matrix is then used as an input for learning 2D DCNN learning which is serially linked to 3D DCNN. Finally, fine-tuned, serially combined DCNN framework is applied for recognizing the identity present in a given test video sequence. To verify the effectiveness of our proposed method, extensive and comparative experiments have been conducted to evaluate our method on COX face databases with their standard face identification protocols. Experimental results showed that our method can achieve better or comparable identification rate compared to other state-of-the-art video FR methods.

Joint Virtual User Identification and Channel Security En/Decoding Method for Ad hoc Network

  • Zhang, Kenan;Li, Xingqian;Ding, Kai;Li, Li
    • International Journal of Computer Science & Network Security
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    • v.22 no.11
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    • pp.241-247
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    • 2022
  • Ad hoc network is self-organized network powered by battery. The reliability of virtual user identification and channel security are reduced when SNR is low due to limited user energy. In order to solve this problem, a joint virtual user identification and channel security en/decoding method is proposed in this paper. Transmitter-receiver-based virtual user identification code is generated by executing XOR operation between orthogonal address code of transmitter and pseudo random address code of receiver and encrypted by channel security code to acquire orthogonal random security sequence so as to improve channel security. In order to spread spectrum as well as improve transmission efficiency, data packet is divided into 6-bit symbols, each symbol is mapped with an orthogonal random security sequence. Subspace-based method is adopted by receiver to process received signal firstly, and then a judgment model is established to identify virtual users according to the previous processing results. Simulation results indicate that the proposed method obtains 1.6dB Eb/N0 gains compared with reference methods when miss alarm rate reaches 10-3.

A Novel Active User Identification Method for Space based Constellation Network

  • Kenan, Zhang;Xingqian, Li;Kai, Ding;Li, Li
    • International Journal of Computer Science & Network Security
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    • v.22 no.12
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    • pp.212-216
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    • 2022
  • Space based constellation network is a kind of ad hoc network in which users are self-organized without center node. In space based constellation network, users are allowed to enter or leave the network at any given time. Thus, the number of active users is an unknown and time-varying parameter, and the performance of the network depends on how accurately this parameter is estimated. The so-called problem of active user identification, which consists of determining the number and identities of users transmitting in space based constellation network is discussed and a novel active user identification method is proposed in this paper. Active user identification code generated by transmitter address code and receiver address code is used to spread spectrum. Subspace-based method is used to process received signal and judgment model is established to identify active users according to the processing results. The proposed method is simulated under AWGN channel, Rician channel and Rayleigh channel respectively. Numerical results indicate that the proposed method obtains at least 1.16dB Eb/N0 gains compared with reference methods when miss alarm rate reaches 10-3.

Video Camera Model Identification System Using Deep Learning (딥 러닝을 이용한 비디오 카메라 모델 판별 시스템)

  • Kim, Dong-Hyun;Lee, Soo-Hyeon;Lee, Hae-Yeoun
    • The Journal of Korean Institute of Information Technology
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    • v.17 no.8
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    • pp.1-9
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    • 2019
  • With the development of imaging information communication technology in modern society, imaging acquisition and mass production technology have developed rapidly. However, crime rates using these technology are increased and forensic studies are conducted to prevent it. Identification techniques for image acquisition devices are studied a lot, but the field is limited to images. In this paper, camera model identification technique for video, not image is proposed. We analyzed video frames using the trained model with images. Through training and analysis by considering the frame characteristics of video, we showed the superiority of the model using the P frame. Then, we presented a video camera model identification system by applying a majority-based decision algorithm. In the experiment using 5 video camera models, we obtained maximum 96.18% accuracy for each frame identification and the proposed video camera model identification system achieved 100% identification rate for each camera model.

Symbol Rate Estimation and Modulation Identification in Satellite Communication System (위성통신시스템에서 심볼율 추정과 변조 방식 구분법)

  • Choi Chan-ho;Lim Jong-bu;Im Gi-hong;Kim Young-wan;Kim Ho-kyom
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.8A
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    • pp.671-678
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    • 2005
  • This paper proposed symbol rate method which does not require a priori knowledge on the symbol rate and simplified modulation identification method to classify BPSK, QPSK, 8PSK signal. In order to estimate the unknown symbol rate, sliding FFT and simple moving average to estimate the spectrum of the signals is utilized, and sliding window and decimation, LPF blcok to estimate the proper symbol rate is used. Although conventional modulation ID method must use SNR value as the test statistics, the receiver cannot estimate the SNR value since the receiver cannot know the modulation type at the start of communication, and bit resolution is high due to using nonlinear function such as log, cosh. Therefore, we proposed the simplified fixed SNR value method. The performance of symbol rate estimation and modulation ID is shown using Monte Carlo computer simulation. This paper show that symbol rate estimation also has good performance in low SNR, and proposed simplified fixed SNR method has almost equivalent performance compared to conventional method.

A Methodology for Urdu Word Segmentation using Ligature and Word Probabilities

  • Khan, Yunus;Nagar, Chetan;Kaushal, Devendra S.
    • International Journal of Ocean System Engineering
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    • v.2 no.1
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    • pp.24-31
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    • 2012
  • This paper introduce a technique for Word segmentation for the handwritten recognition of Urdu script. Word segmentation or word tokenization is a primary technique for understanding the sentences written in Urdu language. Several techniques are available for word segmentation in other languages but not much work has been done for word segmentation of Urdu Optical Character Recognition (OCR) System. A method is proposed for word segmentation in this paper. It finds the boundaries of words in a sequence of ligatures using probabilistic formulas, by utilizing the knowledge of collocation of ligatures and words in the corpus. The word identification rate using this technique is 97.10% with 66.63% unknown words identification rate.

Identification and Control of Electro-Hydraulic Servo System Using DDV

  • Kim, Seung-Hyun;Lee, Chang-Don;Lee, Jin-Kul;Lee, Sang-Hoon
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.169.1-169
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    • 2001
  • In general, for high performance pressure control system, hydraulic system with electo hydraulic servo valve controls flow rate, it contains many nonlinear term like square-root and change of bulk modulus by flow rate. But, DDV(Direct Drive Valve) contains pressure control loop itself, then it can eliminate nonlinearity and achieve linearity for hydraulic system. In this paper, parameter identification method which uses input and ouput data is applied to obtain DDV's mathematical model and parameter assuming that dynamic characteristic of DDV is first order system. Then, the state feedback controller was designed to implement the force control of hydraulic system , and the control performance was evaluated.

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