• Title/Summary/Keyword: recognition-rate

Search Result 2,809, Processing Time 0.03 seconds

Renewable Iris Authentication Algorithm in Mobile System

  • Lee Kwang Je;Lee Soon Seok;Kim Sin Hong;Cho Do Hyun
    • Proceedings of the IEEK Conference
    • /
    • 2004.08c
    • /
    • pp.592-595
    • /
    • 2004
  • Recently the numbers of patent about the technology for mobile payment with Ie or bluetooth-chip are being increased more and more. The reasons of patent increment for mobile payment are advancement of wireless internet technology and rising of customer's request for it. The customer wants to be able to pay for purchase, tax and aid with own mobile phone. So every mobile service provider applies for patents about that competitively. And in the near future the biometrics is generalized in the mobile payment system. Especially the payment service of iris recognition is significant technique in this area for the future prospect. The biometrics of iris is an accurate authentication method because it has about 250 distinguish parameters to the finger print's 30. The biometrics of iris can recognize and identify a person for 2 seconds. But the image of iris is changed by transformation of body in the life. And the existing iris authentication system has problem that can be miss-recognized. In this paper, we propose the new method that reduces miss-recognizing rate with Renewable Iris Authentication Algorithm(RIAA) in mobile system.

  • PDF

SVM Based Speaker Verification Using Sparse Maximum A Posteriori Adaptation

  • Kim, Younggwan;Roh, Jaeyoung;Kim, Hoirin
    • IEIE Transactions on Smart Processing and Computing
    • /
    • v.2 no.5
    • /
    • pp.277-281
    • /
    • 2013
  • Modern speaker verification systems based on support vector machines (SVMs) use Gaussian mixture model (GMM) supervectors as their input feature vectors, and the maximum a posteriori (MAP) adaptation is a conventional method for generating speaker-dependent GMMs by adapting a universal background model (UBM). MAP adaptation requires the appropriate amount of input utterance due to the number of model parameters to be estimated. On the other hand, with limited utterances, unreliable MAP adaptation can be performed, which causes adaptation noise even though the Bayesian priors used in the MAP adaptation smooth the movements between the UBM and speaker dependent GMMs. This paper proposes a sparse MAP adaptation method, which is known to perform well in the automatic speech recognition area. By introducing sparse MAP adaptation to the GMM-SVM-based speaker verification system, the adaptation noise can be mitigated effectively. The proposed method utilizes the L0 norm as a regularizer to induce sparsity. The experimental results on the TIMIT database showed that the sparse MAP-based GMM-SVM speaker verification system yields a 42.6% relative reduction in the equal error rate with few additional computations.

  • PDF

Design of Virtual Reality content for supervising abusement

  • Kim, Minji;Lim, Chan
    • International journal of advanced smart convergence
    • /
    • v.8 no.4
    • /
    • pp.9-15
    • /
    • 2019
  • The government has defined domestic violence as one of the four major social evils and tried to prepare laws and systems to prevent it. Nevertheless, domestic violence has emerged as a serious social issue, and compare to the number of domestic violence cases that are constantly increasing, the report rate of domestic violence is significantly lower. This suggests the need to improve citizens' perception of domestic violence as the issue to solve it together in society, not as a private matter at home. Most of existing contents for preventing domestic violence and improving awareness are simple viewing forms of video contents, which have little effect on recognition. We aim to confirm the possibility of improving social awareness about domestic violence by producing Virtual Reality (VR) contents that have great features of user's immersion and empathy. In this VR content, the user can interact with various objects in the virtual reality of domestic violence and directly or indirectly experience the victim's position. Users who view the violent environment from the victim's point of view can have a subjective empathy for the problem, which is expected to induce more active awareness about domestic violence.

Design and Implementation of a Subjective-type Evaluation System Using Natural Language Processing Technique (유의어 사전을 이용한 주관식 문제 채점 시스템 설계 및 구현)

  • Park, HeeJung;Kang, WonSeog
    • The Journal of Korean Association of Computer Education
    • /
    • v.6 no.3
    • /
    • pp.207-216
    • /
    • 2003
  • An instructor in education generally takes the objective-type evaluation for grading. The subjective-type evaluation has the merit that it can estimate the high-recognition ability, but the problem of the objectivity and reliability of the evaluation. This paper proposes the model which grades for the subjective-type evaluation. and designs and implements the evaluation system using the synonym thesaurus. This system can process the diverse and wide subjective-type questions and provide the easy usage for a beginner. It also can reduce the time and endeavor for evaluation and provide the objectivity of the evaluation. The system results the 73% success rate. We expect that this system will become a basis of the research on the subjective-type evaluation.

  • PDF

Realtime Smoke Detection using Hidden Markov Model and DWT (은닉마르코프모델과 DWT를 이용한 실시간 연기 검출)

  • Kim, Hyung-O
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
    • /
    • v.9 no.4
    • /
    • pp.343-350
    • /
    • 2016
  • In this paper, We proposed a realtime smoke detection using hidden markov model and DWT. The smoke type is not clear. The color of the smoke, form, spread direction, etc., are characterized by varying the environment. Therefore, smoke detection using specific information has a high error rate detection. Dynamic Object Detection was used a robust foreground extraction method to environmental changes. Smoke recognition is used to integrate the color, shape, DWT energy information of the detected object. The proposed method is a real-time processing by having the average processing speed of 30fps. The average detection time is about 7 seconds, it is possible to detect early rapid.

Discrimination between steam processed and unprocessed Tubers of Gastrodia elata Blume by HPLC

  • Zhao, Bing Tian;Song, Si Whan;Le, Duc Dat;Ma, Eun Sook;Son, Jong Keun;Woo, Mi Hee
    • Analytical Science and Technology
    • /
    • v.32 no.6
    • /
    • pp.217-224
    • /
    • 2019
  • In this study, to evaluate the effectiveness and safety of oral therapy using Gastrodiae Rhizoma, a new HPLC-PDA analysis method was developed for the simultaneous quantitation of the three major components: (1) gastrodin, (2) gastrodigenin, and (3) p-hydroxybenzaldehyde, in steam processed and unprocessed tubers of Gastrodia elata Blume. The clear separation of the three components was achieved on a C18 column (250 × 4.6 mm, 5 ㎛) by gradient elution using water (including 0.1 % formic acid) and acetonitrile as the mobile phase. The flow rate was 1.0 mL/min, and the UV detector wavelength was set at 270 nm. The results demonstrate satisfactory linearity, recovery, precision, accuracy, stability, and robustness. The established HPLC-PDA method was applied to quantify three major compounds in 59 samples of G. elata Blume tubers. Finally, the steam processed and unprocessed tubers of G. elata Blume were successfully distinguished by pattern recognition analysis.

RFID Information Protection using Biometric Information (생체정보를 이용한 RFID 정보보호)

  • Ahn, Hyo-Chang;Rhee, Sang-Burm
    • Journal of the Korea Computer Industry Society
    • /
    • v.7 no.5
    • /
    • pp.545-554
    • /
    • 2006
  • RFID could be applied in the various fields such as distribution beside, circulation, traffic and environment on information communication outside. So this can speak as point of ubiquitous computing's next generation technology. However, it is discussed problem of RFID security recently, so we must prepare thoroughly about RFID security for secure information. In this paper, we proposed a method which could protect private information and ensure RFID's identification effectively storing face feature information on RFID tag. Our method which is improved linear discriminant analysis has reduced dimension of feature information which has large size of data. Therefore, we can sore face feature information in small memory field of RFID tag. Our propose d algorithm has shown 92% recognition rate in experimental results and can be applied to entrance control management system, digital identification card and others.

  • PDF

Effective Combination of Temporal Information and Linear Transformation of Feature Vector in Speaker Verification (화자확인에서 특징벡터의 순시 정보와 선형 변환의 효과적인 적용)

  • Seo, Chang-Woo;Zhao, Mei-Hua;Lim, Young-Hwan;Jeon, Sung-Chae
    • Phonetics and Speech Sciences
    • /
    • v.1 no.4
    • /
    • pp.127-132
    • /
    • 2009
  • The feature vectors which are used in conventional speaker recognition (SR) systems may have many correlations between their neighbors. To improve the performance of the SR, many researchers adopted linear transformation method like principal component analysis (PCA). In general, the linear transformation of the feature vectors is based on concatenated form of the static features and their dynamic features. However, the linear transformation which based on both the static features and their dynamic features is more complex than that based on the static features alone due to the high order of the features. To overcome these problems, we propose an efficient method that applies linear transformation and temporal information of the features to reduce complexity and improve the performance in speaker verification (SV). The proposed method first performs a linear transformation by PCA coefficients. The delta parameters for temporal information are then obtained from the transformed features. The proposed method only requires 1/4 in the size of the covariance matrix compared with adding the static and their dynamic features for PCA coefficients. Also, the delta parameters are extracted from the linearly transformed features after the reduction of dimension in the static features. Compared with the PCA and conventional methods in terms of equal error rate (EER) in SV, the proposed method shows better performance while requiring less storage space and complexity.

  • PDF

Personal Biometric Identification based on ECG Features (ECG 특징추출 기반 개인 바이오 인식)

  • Yoon, Seok-Joo;Kim, Gwang-Jun
    • The Journal of the Korea institute of electronic communication sciences
    • /
    • v.10 no.4
    • /
    • pp.521-526
    • /
    • 2015
  • Research on how to use the biological characteristics of human to confirm the identity of the individual is being actively conducted. Electrocardiogram(: ECG) based biometric system is difficult to counterfeit and does not cause skin irritation on the subject. It can be easily combined with conventional biometrics such as fingerprint and face recognition to give multimodal biometric systems. In this thesis, biometric identification method analysing ECG waveform characteristics from Discrete Wavelet Transform(DWT) coefficients is suggested. Feature selection is performed on the 9 coefficients of DWT using the correlation analysis. The verification is achieved by using the error back propagation neural networks. Using the proposed approach on 24 subjects of MIT-BIH QT Database, 98.88% verification rate has been obtained.

Rolled Fingerprint Merge Algorithm Using Adaptive Projection Mask (가변 투영마스크를 이용한 회전지문 정합 알고리즘에 관한 연구)

  • Baek, Young Hyun
    • Journal of the Institute of Electronics and Information Engineers
    • /
    • v.50 no.12
    • /
    • pp.176-183
    • /
    • 2013
  • We propose a rolled fingerprint merging algorithm that effectively merges plain fingerprints in consecutive frame units that are fed through rolling and detects more fingerprint minutiae in order to increase the fingerprint recognition rate. The proposed rolled fingerprint merging algorithm uses a adaptive projection mask; it contains a detector that separates plain fingerprints from the background and a projection mask generator that sequentially projects the detect ed images. In addition, in the merging unit, the pyramid-shaped projection method is used to detect merged rolled fingerprints from the generated variable projective mask, starting from the main images. Simulations show that the extracted minutia e are 46.79% more than those from plain fingerprints, and the proposed algorithm exhibits excellent performance by detecting 52.0% more good fingerprint minutiae that are needed for matching.