• The KIPS Transactions:PartB
• /
• v.12B no.2 s.98
• /
• pp.123-130
• /
• 2005

In this paper, fingerprint identification algorithm using pixel direction factor in blocks is proposed to minimize false acceptance ratio and to apply security system. The proposed algorithm is that a fingerprint image is divided by 16 blocks, then feature parameters which have direct factors of $0^{\circ},\;45^{\circ},\;90^{\circ}\;and\;135^{\circ}$ is extracted for each block. Membership function of a reference fingerprint and an input fingerprint for the extracted parameters is calculated, then identification of two fingerprint is distinguished using fuzzy inference. False acceptance ratio is evaluated about different fingerprints of In kinds regardless of sex and shape which are obtained from adults, and false rejection ratio is evaluated about fingerprints which are obtained by adding fingerprints of 10 kinds on different fingerprints of 100 kinds. The experiment results is that false acceptance ratio is average $0.34\%$ about experiment of 4,950 times, and false rejection ratio is average $3.7\%$ about experiment of 1,000 times. The proposed algerian is excellent for recognition rate and security.

• The Journal of the Acoustical Society of Korea
• /
• v.20 no.7
• /
• pp.69-75
• /
• 2001

Intra-speaker variation, noise environments, and mismatch between training and test conditions are the major reasons for the speaker verification system unable to use it practically. In this study, we propose robust end-point detection algorithm, noise cancelling with the microphone property compensation technique, and inter-speaker discriminate technique by weighting cepstrum for robust speaker verification system. Simulation results show that the average speaker verification rate is improved in the rate of 17.65% with proposed end-point detection algorithm using LPC residue and is improved in the rate of 36.93% with proposed noise cancelling and microphone property compensation algorithm. The proposed weighting function for discriminating inter-speaker variations also improves the average speaker verification rate in the rate of 6.515%.

• 전자공학회논문지 IE
• /
• v.49 no.2
• /
• pp.9-17
• /
• 2012

One of the problems on the application of the speech recognition system in the real world is the degradation of the performance by acoustical distortions. The most important source of acoustical distortion is the additive noise. This paper describes a spectral compensation technique based on a spectral peak enhancement scheme followed by an efficient noise subtraction scheme for noise robust speech recognition. The proposed methods emphasize the formant structure and compensate the spectral tilt of the speech spectrum while maintaining broad-bandwidth spectral components. The recognition experiments was conducted using noisy speech corrupted by white Gaussian noise, car noise, babble noise or subway noise. The new technique reduced the average error rate slightly under high SNR(Signal to Noise Ratio) environment, and significantly reduced the average error rate by 1/2 under low SNR(10 dB) environment when compared with the case of without spectral compensations.

• The Journal of the Acoustical Society of Korea
• /
• v.21 no.4
• /
• pp.394-400
• /
• 2002

In digital speech communications, the quality of service can be increased by speech coding scheme that is adaptive to the error rate of voice packet transmission. However, current communication protocol in cellular and internet communications does not provide the function that transmits the channel error information. To solute this problem, in this paper, new method for real-time transmission of channel error information is proposed, where channel error information is embedded in voice packet. The proposed method utilizes the pulse positions of codevector in ACELP speech codec, which results in little degradation in speech quality and low false alarm rate. The simulations with various speech data show that the proposed method meets the requirement in speech quality, detection rate, and false alarm rate.

• Proceedings of the Korean Information Science Society Conference
• /
• 2001.10b
• /
• pp.157-159
• /
• 2001

신경 트리는 신경망과 결정 트리의 구조를 결합한 형태의 분류기로서 비선형적 결정 경계 형성이 가능하며 기존 신경망에 비해 학습, 출력시 계산량이 적다는 장점을 갖는다. 본 논문에서는 신경 트리의 노드를 구성하는 신경망을 학습하기 위하여 기존의 방법들과는 달리 교사 학습 방법인 LVQ3 알고리즘을 사용하는 신경 트리 분류기를 제안한다. 학습 과정을 통해 생성된 트리는 오인식율 추정을 이용한 가지치기를 통하여 효율적인 트리로 재구성된다. 제안하는 방법은 실제 데이터 집합들을 이용한 실험을 통하여 그 성능을 검증하였다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2015.07a
• /
• pp.187-190
• /
• 2015

주행 중 차선 이탈 경고 시스템은 사고 발생 예방 차원에서 매우 높은 효과가 인정되어서 차선이탈 경고 장치(LDWS) 제품들이 출시되고 있다. 본 논문은 블랙박스의 영상을 이용하여 차선 검출에 정확도를 향상하기 위한 알고리즘을 연구한 것으로 특히 차량에 장착되어 있는 블랙박스 영상을 영상 변환 없이, 실시간 소프트웨어 만 으로 처리할 수 있는 알고리즘을 연구한다. 차선인식을 위한 최적의 영상 ROI를 결정하고, 차선 인식 정확도를 향상하기 위한 전 처리 과정을 적용하고, 동영상의 연속성을 잘못된 차선인식에 대한 보정, 인식이 되지 않는 차선에 대한 후보 차선 추천 알고리즘과 시점 변환에 의한 야간, 곡선 도로에 대한 오인식율을 최소화 하는 방법을 제안한다. 도로주행의 다양한 환경에 대한 실험을 진행했으며, 각각의 방법 적용에 의한 오인식율의 감소와 많은 인식 알고리즘 적용에 의한 처리 속도 저하를 개선하기 위한 연구를 진행했으며, 본 논문은 블랙박스 영상을 이용하여 주행 차선 인식을 위한 최적 알고리즘을 제안한다.

• Proceedings of the IEEK Conference
• /
• 2001.09a
• /
• pp.503-506
• /
• 2001

In this paper, we describe the implementation of a microphone input level control algorithm and the speech improvement with this level controller in personal computer environment. The volume of speech obtained through a microphone affects the speech recognition rate directly. Therefore, proper input volume level control is desired fur better recognition. We considered some conditions for the successful volume controller implementation firstly, then checked its usefulness on our speech recognition system with common office environment speech database. Cepstral mean subtraction is also utilized far the channel-effect compensation of the database. Our implemented controller achieved approximately 50% reduction, i.e., improvement in speech recognition error rate.

• The Journal of the Korea Contents Association
• /
• v.5 no.5
• /
• pp.33-42
• /
• 2005

In this paper, we propose a new training algorithm for improving pattern classification performance of ART neural network. The proposed train algorithm restricts unnecessary cluster generation and transition, applies the location extraction algorithm, and operates the reset system based on the agreement between the present learning pattern and the initial pattern. As a result, repetitive input of a pattern does not generate a new cluster and mis-recognition rate decreases.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.6
• /
• pp.1140-1148
• /
• 1994

In this paper, we carried out some experiments on the Korean vowel recognition using the fractal dimension of the speech signals. We chose the Minkowski-Bouligand dimension as the fractal dimension, and computed it using the morphological covering method. For our experiments, we used both the fractal dimension and the LPC cepstrum which is conventionally known to be one of the best parameters for speech recognition, and examined the usefulness of the fractal dimension. From the vowel recognition experiments under various consonant contexts, we achieved the vowel recognition error rates of 5.6% and 3.2% for the case with only LPC cepstrum and that with both LPC cepstrum and the fractal dimension, respectively. The results indicate that the incorporation of the fractal dimension with LPC cepstrum gives more than 40% reduction in recognition errors, and indicates that the fractal dimension is a useful feature parameter for speech recognition.

• Smart Media Journal
• /
• v.3 no.3
• /
• pp.15-19
• /
• 2014

Fingerprint Recognition System is made up of Off-line treatment and On-line treatment; the one is registering all the information of there trier features which are retrieved in the digitalized fingerprint getting out of the analog fingerprint through the fingerprint acquisition device and the other is the treatment making the decision whether the users are approved to be accessed to the system or not with matching them with the fingerprint features which are retrieved and database from the input fingerprint when the users are approaching the system to use. In this paper, Among various biometrics recognition systems, statistical fingerprint recognition matching methods are considered using minutiae on fingerprints. We define similarity distance measures based on the coordinate and angle of the minutiae, and suggest a fingerprint recognition model following statistical distributions.