• Journal of Broadcast Engineering
• /
• v.17 no.4
• /
• pp.659-669
• /
• 2012

This paper proposes the method to extract a binary audio fingerprint by combining several base binary fingerprints. Based on majority voting of base fingerprints, which are designed by mimicking the fingerprint used in Philips fingerprinting system, the proposed fingerprint is determined. In the matching part, the base fingerprints are extracted from the query, and distance is computed using the sum of them. In the experiments, the proposed fingerprint outperforms the base binary fingerprints. The method can be used for enhancing the existing binary fingerprint or for designing a new fingerprint.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.10b
• /
• pp.278-283
• /
• 2006

결정 트리는 큰 가설 공간을 가지고 있어 유연하고 강인한 성능을 지닐 수 있다. 하지만 결정트리가 학습 데이터에 지나치게 적응되는 경향이 있다. 학습데이터에 과도하게 적응되는 경향을 없애기 위해 몇몇 가지치기 알고리즘이 개발되었다. 하지만, 데이터가 속성 축에 평행하지 않아서 오는 공간 낭비의 문제는 이러한 방법으로 해결할 수 없다. 따라서 본 논문에서는 다변수 노드를 사용한 선형 분류기를 이용하여 이러한 문제점을 해결하는 방법을 제시하였으며, 결정트리의 성능을 높이고자 지지 벡터 머신을 도입하였다(SVMDT). 본 논문에서 제시한 알고리즘은 세 가지 부분으로 이루어졌다. 첫째로, 각 노드에서 사용할 속성을 선택하는 부분과 둘째로, ID3를 이 목적에 맞게 바꾼 알고리즘과 마지막으로 기본적인 형태의 가지치기 알고리즘을 개발하였다. UCI 데이터 셋을 이용하여 OC1, C4.5, SVM과 비교한 결과, SVMDT는 개선된 결과를 보였다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.8C
• /
• pp.814-821
• /
• 2009

In an ultrawide band (UWB) indoor wireless localization, time of arrival (TOA) parameter estimation techniques have some difficulties in acquiring a reasonable TOA estimate because of the clustered multipath components overlapping or random time intervals mainly due to non line-of-sight (NLOS) environment. In order to solve that problem and achieve an excellent UWB indoor wireless localization, we propose a UWB signal model and a robust TOA parameter estimation technique that has little effect on the clustered problems unlike the conventional technique. Through simulation studies, the validity of the proposed model and the TOA estimation technique are examined. The performance of estimation error is also analyzed.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.9C
• /
• pp.748-755
• /
• 2010

In this paper we propose an improved face recognition method using Gabor tensor. Gabor transform is known to be able to represent characteristic feature in face and reduced environmental influence. It may contribute to improve face recognition ratio. We attempted to combine three-dimensional tensor from Gabor transform with MPCA(Multilinear PCA) and LDA. MPCA with tensor which use various features is more effective than traditional one or two dimensional PCA. It is known to be robust to the change of face expression or light. Proposed method is simulated by MATALB9 using ORL and Yale face database. Test result shows that recognition ratio is improved maximum 9~27% compared with exisisting face recognition method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2012.07a
• /
• pp.271-274
• /
• 2012

음성 신호처리에서 많이 쓰이는 음성구간 검출은 주로 음향신호의 분석을 통하여 음향 신호에 음성이 존재하는지 여부를 판단한다. 그러나 음향신호를 이용한 방법은 음성 또는 비음성 잡음이나 주위 음향 환경에 의하여 성능이 결정된다는 단점이 있다. 음향 환경 변화에 강인한 음성구간 검출을 수행하기 위하여, 영상정보를 이용한 음성구간 검출 방법들이 최근에 연구되어 왔는데 기존 방법들은 입술 모양의 변화를 추정하기 위하여 입술 모델 등을 이용하거나 구강(oral cavity) 영역에 해당하는 픽셀 수의 변화를 이용하여 음성 구간을 검출하였다. 위 방법들은 입술의 모양을 추정하는 데 복잡한 계산이 필요하거나, 입술 모양 추정 없이 구강 영역픽셀 수만 이용하기 때문에 다소 정확도가 떨어진다는 단점이 있다. 본 논문에서는, 입술 모양의 변화를 추정하기 위해 밖으로 드러나는 구강 영역의 모양을 타원 근사법으로 추정하고, 타원의 넓이와 높이의 변화를 이용하여 음성 구간을 검출하는 방법을 제안하였다. 비교 실험 결과, 제안하는 방법은 구강영역 픽셀 수의 변화만 이용하는 방법에 비해 우수한 성능을 보임을 확인할 수 있었다.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.44 no.4
• /
• pp.308-315
• /
• 2016

A new technique for Attitude & Heading Reference System (AHRS) by using sequential measurement noise covariance (SMNC) is addressed in a vibration environments in this paper. In particular, a low-cost inertial measurement unit in general diverges in the acceleration phase or vibrating environments due to inherent properties of gravity and acceleration. In this paper, by considering current and prior measurements to estimate actual attitudes and headings in a local frame, the proposed technique overcomes these problems efficiently. Finally, the performance of the suggested approach is verified by numerical simulations.

• Journal of Broadcast Engineering
• /
• v.21 no.2
• /
• pp.268-271
• /
• 2016

In video sequences, foreground object detection being composed of a background model and a background subtraction is an important part of diverse computer vision applications. However, object detection might fail in sudden illumination changes. In this letter, an illumination-robust background detection is proposed to address this problem. The method can provide quick adaption to current illumination condition using two background models with different adaption rates. Since the proposed method is a non-parametric approach, experimental results show that the proposed algorithm outperforms several state-of-art non-parametric approaches and provides low computational cost.

• The Journal of the Acoustical Society of Korea
• /
• v.24 no.4
• /
• pp.224-229
• /
• 2005

In this paper, we Propose a novel cepstrum normalization method which normalizes the probability density function (pdf) of cepstrum for robust speech recognition in additive noise environments. While the conventional methods normalize the first- and/or second-order statistics such as the mean and/or variance of the cepstrum. the proposed method fully normalizes the statistics of cepstrum by making the pdfs of clean and noisy cepstrum identical to each other For the target Pdf, the generalized Gaussian distribution is selected to consider various densities. In recognition phase, we devise a table lookup method to save computational costs. From the speaker-independent isolated-word recognition experiments, we show that the Proposed method gives improved Performance compared with that of the conventional methods, especially in heavy noise environments.

• Journal of KIISE
• /
• v.42 no.12
• /
• pp.1544-1550
• /
• 2015

Recently, the development of practical wearable robot interfaces has resulted in the emergence of wearable robots such as arm prosthetics or lower-limb exoskeletons. In this paper, we propose a novel method of wrist movement intention estimation based on a regression technique using electromyography of human bio-signals. In daily life, changes in user arm position changes cause decreases in performance by modulating EMG signals. Therefore, we propose an estimation method for robust wrist movement intention for arm position changes, combining several movement intention models based on the regression technique trained by different arm positions. In our experimental results, our method estimates wrist movement intention more accurately than previous methods.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2000.10b
• /
• pp.1263-1266
• /
• 2000

In this paper, we propose a reliable Image transmission system with Decision Feedback Equalization (DFE), and use diversity combining techniques over multipath fading channels. It is shown that the proposed system has the features of simplicity in implementation with DFE and diversity combining techniques without modifying DFE. This study includes error concealment techniques for reconstruction of missing blocks in JPEG. To verify and compare the performance of our proposed system, the computer simulations have been performed in three diversity combining cases.