• Title/Summary/Keyword: FRR

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Facial Feature Verification System based on SVM Classifier (SVM 분류기에 의한 얼굴 특징 식별 시스템)

  • Park Kang Ryoung;Kim Jaihie;Lee Soo-youn
    • The KIPS Transactions:PartB
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    • v.11B no.6
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    • pp.675-682
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    • 2004
  • With the five-day workweek system in bank and the increased usage of ATM(Automatic Toller Machine), it is required that the financial crime using stolen credit card should be prevented. Though a CCTV camera is usually installed in near ATM, an intelligent criminal can cheat it disguising himself with sunglass or mask. In this paper, we propose facial feature verification system which can detect whether the user's face can be Identified or not, using image processing algorithm and SVM(Support Vector Machine). Experimental results show that FAR(Error Rate for accepting a disguised man as a non-disguised one) is 1% and FRR(Error Rate for rejecting a normal/non-disguised man as a disguised one) is 2% for training data. In addition, it shows the FAR of 2.5% and the FRR of 1.43% for test data.

Contactless Biometric Using Thumb Image (엄지손가락 영상을 이용한 비접촉식 바이오인식)

  • Lim, Naeun;Han, Jae Hyun;Lee, Eui Chul
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.12
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    • pp.671-676
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    • 2016
  • Recently, according to the limelight of Fintech, simple payment using biometric at smartphone is widely used. In this paper, we propose a new contactless biometric method using thumb image without additional sensors unlike previous biometrics such as fingerprint, iris, and vein recognition. In our method, length, width, and skin texture information are used as features. For that, illumination normalization, skin region segmentation, size normalization and alignment procedures are sequentially performed from the captured thumb image. Then, correlation coefficient is calculated for similarity measurement. To analyze recognition accuracy, genuine and imposter matchings are performed. At result, we confirmed the FAR of 1.68% at the FRR of 1.55%. In here, because the distribution of imposter matching is almost normal distribution, our method has the advantage of low FAR. That is, because 0% FAR can be achieved at the FRR of 15%, the proposed method is enough to 1:1 matching for payment verification.

A Study of Vein Identification System using 2D-Gabor Filter for the Vessel USN Entrance/Exit Management (선박USN 출입관리를 위한 2차원 Gabor 필터를 이용한 정맥 인식 방법에 관한 연구)

  • Choi, Myeong-Soo;Lee, Seong-Ro;Sin, Sang-Woo;Jang, Kyung-Sik;Jung, Min-A
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.11A
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    • pp.1190-1196
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    • 2007
  • In this paper, we propose the biometrics system using hand vein pattern. This system is for management about person's entrance/exit in vessel USN. we select the biometrics method using hand vein pattern as adoptable method to vessel USN environment. Our experimental results show that preprocessing using two dimensional gabor filter achieves performance improvements over high pass filtering. Also, we compared our method with measured FAR(False Acceptance Rate) and FRR(False Rejection Rate) using pattern matching, the results show low error rate over high pass filtering. As a result, we verify the adoptability of biometrics system using hand vein pattern in management of person's entrance/exit in vessel.

A Study of User Behavior Recognition-Based PIN Entry Using Machine Learning Technique (머신러닝을 이용한 사용자 행동 인식 기반의 PIN 입력 기법 연구)

  • Jung, Changhun;Dagvatur, Zayabaatar;Jang, RhongHo;Nyang, DaeHun;Lee, KyungHee
    • KIPS Transactions on Computer and Communication Systems
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    • v.7 no.5
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    • pp.127-136
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    • 2018
  • In this paper, we propose a PIN entry method that combines with machine learning technique on smartphone. We use not only a PIN but also touch time intervals and locations as factors to identify whether the user is correct or not. In the user registration phase, a remote server was used to train/create a machine learning model using data that collected from end-user device (i.e. smartphone). In the user authentication phase, the pre-trained model and the saved PIN was used to decide the authentication success or failure. We examined that there is no big inconvenience to use this technique (FRR: 0%) and more secure than the previous PIN entry techniques (FAR : 0%), through usability and security experiments, as a result we could confirm that this technique can be used sufficiently. In addition, we examined that a security incident is unlikely to occur (FAR: 5%) even if the PIN is leaked through the shoulder surfing attack experiments.

Cloning and Characterization of the pyrH Gene Encoding UMP-Kinase from Lactobacillus reuteri ATCC 55739

  • PARK JAE-YONG;NAM SU JIN;KIM JONG-HWAN;JEONG SEON-JU;KIM JUNG KON;HA YEONG LAE;KIM JEONG HWAN
    • Journal of Microbiology and Biotechnology
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    • v.15 no.3
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    • pp.525-531
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    • 2005
  • From a genomic library of Lactobacillus reuteri ATCC 55739, one clone, NE347, carrying a pyrH gene encoding UMP kinase, was identified. pNE347 carried a 1.88 kb EcoRI fragment and the pyrH was located in the middle of the insert. pyrH ORF was 723 bp in size and capable of encoding UMP kinase composed of 240 amino acid residues. tsf encoding an elongation factor-Ts and frr encoding a ribosomal recycling factor were present upstream and downstream of pyrH, respectively. When introduced into E. coli KUR1244, a pyrH-negative strain, pNE347 restored the ability to grow at $42^{\circ}C$, indicating that pyrH from L. reuteri synthesized functional UMP kinase in E. coli. Northern blot experiment showed that pyrH and frr were cotranscribed as a 1.4 kb single transcript. pyrH was overexpressed in E. coli by using a pET26b(+) vector, and a major 25 kDa protein band appeared on SDS-polyacrylamide gel.

System-level Analysis of a Fan-motor Assembly for Vacuum Cleaner (진공청소기용 팬-모터 어셈블리의 시스템-레벨 분석)

  • Park, Chang-Hwan;Park, Kyung-Hyun;Chang, Kyung-Sik
    • The KSFM Journal of Fluid Machinery
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    • v.20 no.1
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    • pp.5-14
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    • 2017
  • A fan-motor assembly in a vacuum cleaner is analyzed through system-level analysis method. This system consisted of three components, a fan, motor, and the flow resistance of the motor, or of the vacuum cleaner. System-level analysis method is characterized by the combination of torque matching at a constant throttling condition between the fan and the motor and the pressure drop at a constant flow rate due to the flow resistance of the motor, or of the vacuum cleaner. The performance characteristics of the fan-motor assembly and the vacuum cleaner system could be predicted over the whole range of operation, based on the characteristics of each component. The predicted performance of the vacuum cleaner system through system-level analysis agreed well with the experimental results within 4.5% difference of pressure and 6% difference of the efficiency. The effect of flow resistance of a motor is investigated and it is found that the efficiency decrease of fan-motor assembly at the constant flow rate due to the flow resistance of a motor is determined by the flow resistance ratio(FRR), which is defined as a ratio of flow resistance of motor and the flow resistance of a constant throttling condition of a given point. The fan-motor assembly(S2 model) was modified to reduce the FRR from 9.0% to 2.4% and the experimental result shows that the efficiency of S2 model was improved by about 3% at best efficiency point.

Multi-Modal Biometries System for Ubiquitous Sensor Network Environment (유비쿼터스 센서 네트워크 환경을 위한 다중 생체인식 시스템)

  • Noh, Jin-Soo;Rhee, Kang-Hyeon
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.44 no.4 s.316
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    • pp.36-44
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    • 2007
  • In this paper, we implement the speech & face recognition system to support various ubiquitous sensor network application services such as switch control, authentication, etc. using wireless audio and image interface. The proposed system is consist of the H/W with audio and image sensor and S/W such as speech recognition algorithm using psychoacoustic model, face recognition algorithm using PCA (Principal Components Analysis) and LDPC (Low Density Parity Check). The proposed speech and face recognition systems are inserted in a HOST PC to use the sensor energy effectively. And improve the accuracy of speech and face recognition, we implement a FEC (Forward Error Correction) system Also, we optimized the simulation coefficient and test environment to effectively remove the wireless channel noises and correcting wireless channel errors. As a result, when the distance that between audio sensor and the source of voice is less then 1.5m FAR and FRR are 0.126% and 7.5% respectively. The face recognition algorithm step is limited 2 times, GAR and FAR are 98.5% and 0.036%.

Optimization of chemical cleaning for reverse osmosis membranes with organic fouling using statistical design tools

  • Park, Ki-Bum;Choi, Changkyoo;Yu, Hye-Weon;Chae, So-Ryong;Kim, In S.
    • Environmental Engineering Research
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    • v.23 no.4
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    • pp.474-484
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    • 2018
  • The cleaning efficiency of reverse osmosis (RO) membranes inevitably fouled by organic foulants depends upon both chemical (type of cleaning agent, concentration of cleaning solution) and physical (cleaning time, flowrate, temperature) parameters. In attempting to determine the optimal procedures for chemical cleaning organic-fouled RO membranes, the design of experiments concept was employed to evaluate key factors and to predict the flux recovery rate (FRR) after chemical cleaning. From experimental results and based on the predicted FRR of cleaning obtained using the Central Composite Design of Minitab 17, a modified regression model equation was established to explain the chemical cleaning efficiency; the resultant regression coefficient ($R^2$) and adjusted $R^2$ were 83.95% and 76.82%, respectively. Then, using the optimized conditions of chemical cleaning derived from the response optimizer tool (cleaning with 0.68 wt% disodium ethylenediaminetetraacetic acid for 20 min at $20^{\circ}C$ with a flowrate of 409 mL/min), a flux recovery of 86.6% was expected. Overall, the results obtained by these experiments confirmed that the equation was adequate for predicting the chemical cleaning efficiency with regards to organic membrane fouling.

Diagnosis of Inter Turn Short Circuit in 3-Phase Induction Motors Using Applied Clarke Transformation (Clarke 변환을 응용한 3상 유도전동기의 Inter Turn Short Circuit 진단)

  • Yeong-Jin Goh;Kyoung-Min Kim
    • Journal of IKEEE
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    • v.27 no.4
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    • pp.518-523
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    • 2023
  • The diagnosis of Inter Turn Short Circuits (ITSC) in induction motors is critical due to the escalating severity of faults resulting from even minor disruptions in the stator windings. However, diagnosing ITSC presents significant challenges due to similarities in noise and losses shared with 3-phase induction motors. Although artificial intelligence techniques have been explored for efficient diagnosis, practical applications heavily rely on model-based methods, necessitating further research to enhance diagnostic performance. This study proposed a diagnostic method applied the Clarke Transformation approach, focusing solely on current components while disregarding changes in rotating flux. Experimental results conducted over a 30-minute period, encompassing both normal and ITSC conditions, demonstrate the effectiveness of the proposed approach, with FAR(False Accept Rates) of 0.2% for normal-to-ITSC FRR(False Rejection Rates) and 0.26% for ITSC-to-normal FRR. These findings underscore the efficacy of the proposed approach.

Translation- and Rotation-Invariant Fingerprint Authentication Based on Gabor Features (Gabor 특징에 기반한 이동 및 회전 불변 지문인증)

  • 김종화;조상현;성효경;최홍문
    • Proceedings of the IEEK Conference
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    • 2000.09a
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    • pp.901-904
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    • 2000
  • A direct authentication from gray-scale image, instead of the conventional multi-step preprocessing, is proposed using Gabor filter-based features from the gray-scale fingerprint around core point. The core point is located as a reference point for the translation invariant matching. And its principal symmetry axis is detected for the rotation invariant matching from its neighboring region centered at the core point. And then fingerprint is divided into non-overlapping blocks with respect to the core point and features are directly extracted form the blocked gray level fingerprint using Gabor filter. The proposed fingerprint authentication is based on the Euclidean distance between the corresponding Gabor features of the input and the template fingerprints. Experiments are conducted on 300${\times}$300 fingerprints obtained from a CMOS sensor with 500 dpi resolution, and the proposed method could lower the False Reject Rate(FRR) to 18.2% under False Acceptance Rate(FAR) of 0%.

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