• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.251-256
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• 2021

Unlike general cameras, a high-speed camera capable of capturing a large number of frames per second can enable the advancement of some image processing technologies that have been limited so far. This paper proposes a method of removing undesirable noise from an high-speed input color image, and then detecting a human face from the noise-free image. In this paper, noise pixels included in the ultrafast input image are first removed by applying a bidirectional filter. Then, using RetinaFace, a region representing the person's personal information is robustly detected from the image where noise was removed. The experimental results show that the described algorithm removes noise from the input image and then robustly detects a human face using the generated model. The model-based face-detection method presented in this paper is expected to be used as basic technology for many practical application fields related to image processing and pattern recognition, such as indoor and outdoor building monitoring, door opening and closing management, and mobile biometric authentication.

• The Journal of the Acoustical Society of Korea
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• v.25 no.6
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• pp.269-276
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• 2006

In this paper, we propose an emotion recognition system that can discriminate human emotional state into neutral or anger from the speech captured by a cellular-phone in real time. In general. the speech through the mobile network contains environment noise and network noise, thus it can causes serious System performance degradation due to the distortion in emotional features of the query speech. In order to minimize the effect of these noise and so improve the system performance, we adopt a simple MA (Moving Average) filter which has relatively simple structure and low computational complexity, to alleviate the distortion in the emotional feature vector. Then a SFS (Sequential Forward Selection) feature optimization method is implemented to further improve and stabilize the system performance. Two pattern recognition method such as k-NN and SVM is compared for emotional state classification. The experimental results indicate that the proposed method provides very stable and successful emotional classification performance such as 86.5%. so that it will be very useful in application areas such as customer call-center.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.1-5
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• 2002

The purpose of this paper is developing a speech recognition module in a wheelchair for the sake of convenience. of the disability. For this system, we used TMS320C32 as a main processor; eliminated noise by applying Winer filler while considering characteristics of noise environment in pre-processing stage, and; extracted 12 feature patterns per france using LPC&Cepstrum. Then, we implemented the hybrid form combining DTW (Dynamic Time Warping), which is generally used for isolated words in the conventional algorithms, in the recognition Part, and NN (Neural network) to prevent any error of recognition. In this research, we achieved a recognition rate of more than 96% on isolated words when DTW and Hybrid forms were individually experimented in noise environment

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06e
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• pp.381-384
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• 1998

본 논문은 주행중인 자동차 환경에서 운전자의 안전성 및 편의성의 동시 확보를 위하여, 보조적인 스위치 조작없이 상시 음성의 입, 출력이 가능하도록 한다. 이때 잡음에 강인한 threshold 값을 구하기 위하여, 일정한 시간마다 기준 에너지와 영교차율(Zero Crossing Rate)을 변경하며, 밴드패스 필터(bandpass filter)를 이용하여 1차, 2차로 나누어 실시간 상태에서 자동으로, 정확하게 끝점검출(End Point Detection)을 처리한다. 기준패턴(reference pattern)은 DMS(Dynamic Multi-Section)을 사용하며, 화자의 변별력을 높이기 위하여 2개의 모델사용을 제안한다. 또한 주행중인 차량의 잡음환경에 강인하기 위하여 일반주행(80km/h 이내), 고속주행(80km/h 이상)등으로 나누며 차량의 가변잡음 크기에 따라 자동으로 선택하도록 한다. 음성의 특징 벡터와 인식 알고리즘은 PLP 13차와 One-Stage Dynamic Programming (OSDP)를 이용한다. 실험결과, 자주 사용되는 차량 편의장치 제어명령 33개에 대하여 중부, 영동 고속도로(시속 80Km/h 이상)에서 화자독립 89.75%, 화자종속 90.08%의 인식율을 구하였으며, 경부 고속도로에서는 화자독립 92.29%, 화자종속 92.42%의 인식율을 구하였다. 그리고 저속 주행중인 자동차 환경(80km/h 이내, 시멘트, 아스팔트 등의 서울시내 및 시외독립)에서는 화자독립 92.89%, 화자종속 94.44% 인식율을 구하였다.

• Journal of Advanced Navigation Technology
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• v.5 no.2
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• pp.111-122
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• 2001

In this paper, we study the performance of eigencanceller which use a eigenvector and eigenvalue in order to update a weighter vector. Eigencanceller can suppress directional interferences and noise effectively while maintaining specified beam pattern constraints. The constraints and optimal weight vector of eigencanceller vary by using interference and noise or desired signal, interference signal and noise as array input signal. From the analysis results in the steady state, We show that weight vectors in each case are simplified the form of projection equation that belongs to desired subspace orthogonal to interference subspace and eigencanceller has the better performance than RLS method through mathematical analysis and simulation.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.807-811
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• 1999

자동 지문 인식을 위한 특징점 추출 과정에서 얻은 특징점에는 지문 획득시 발생하는 잡음과 전처리 과정으로 인한 정보의 손실에 의해 상당량의 의사 특징점이 포함되어 있다. 본 논문에서는 특징점들로 구성된 지문의 특징량에서 잡음이라고 할 수 있는 의사 특징점을 제거하는 알고리즘을 제안한다. 제안하는 알고리즘은 후보 특징점 목록에서 세선화된 지문 화상의 구조적 특성을 고려하여 복원 가능 영역에 속하고 의사 특징점이라고 간주되는 특징점을 선택한다. 이와 같이 선택된 특징점이 세선화 화상에 위치하는 영역은 잡음에 의해 잘못 세선화된 부분이기 때문에 해당 영역을 올바르게 재구성하고 후보 특징점 목록에서 선택한 특징점을 삭제한다. 재구성된 세선화 화상에서 지문 원화상의 부영역별 방향과 지문의 구조적 특성을 근거로 후보 특징점이 위치한 영역의 패턴을 검사하여 진짜 특징점만을 선택함으로써 의사 특징점을 제거하게 된다. NIST sdb 14의 지문 화상을 알고리즘에 적용한 결과는 정추출율 손실 대비 높은 오추출율 개선을 얻었음을 보여주고 있다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.2
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• pp.10-20
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• 2002

Various blind source separation (BSS) and independent component analysis (ICA) algorithms have been developed. However, comparison study for BSS/ICA algorithms has not been extensively carried out yet. The main objective of this paper is to compare various promising BSS/ICA algorithms in terms of several factors such as robustness to sensor noise, computational complexity, the conditioning of the mixing matrix, the number of sensors, and the number of training patterns. We propose several benchmarks which are useful for the evaluation of the algorithm. This comparison study will be useful for real-world applications, especially EEG/MEG analysis and separation of miked speech signals.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.5
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• pp.694-704
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• 2001

In this work, We evaluate the performance of eigencanceller which can suppress directional interferences and noise effectively while maintaining specified beam pattern constraints. The constraints and optimal weight vector of eigencanceller vary by using interference and noise or desired signal, interference and noise as array input signal. From the analysis results in the steady state, We show that weight vectors in each case are simplified the form of projection equation that belongs to desired subspace orthogonal to interference subspace and eigencanceller has the better performance than DMI method through mathematical analysis and simulation.

• The Journal of the Acoustical Society of Korea
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• v.32 no.2
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• pp.147-156
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• 2013

In this paper, a new speech endpoint detection method in noisy environments for moving robot platforms is proposed. In the conventional method, the endpoint of speech is obtained by applying an edge detection filter that finds abrupt changes in the feature domain. However, since the feature of the frame energy is unstable in such noisy environments, it is difficult to accurately find the endpoint of speech. Therefore, a novel feature extraction method based on the twice-iterated fast fourier transform (TIFFT) and statistical models of speech is proposed. The proposed feature extraction method was applied to an edge detection filter for effective detection of the endpoint of speech. Representative experiments claim that there was a substantial improvement over the conventional method.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.2
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• pp.343-348
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• 2020

During 50 years, the chaotic theory has begun to research with concerning in Mathematics and physics, and it has extended the fields to of engineering and social science. Recently, chaotic theory has progressed as a type of fusion research fused with natural science and social science. Such fused research includes problems for addiction, happiness of human, problem happened between family and love affairs between man and woman. In this paper, we consider the external environment based on love model which is one among fusion research, and when we consider colored noise in the external environment, we verify how the chaotic pattern is affected in the love model through time series and phase portrait.