• 제목/요약/키워드: 웨이블릿 분석

검색결과 249건 처리시간 0.031초

Robust Face Recognition Against Illumination Change Using Visible and Infrared Images (가시광선 영상과 적외선 영상의 융합을 이용한 조명변화에 강인한 얼굴 인식)

  • Kim, Sa-Mun;Lee, Dea-Jong;Song, Chang-Kyu;Chun, Myung-Geun
    • Journal of the Korean Institute of Intelligent Systems
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    • 제24권4호
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    • pp.343-348
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    • 2014
  • Face recognition system has advanctage to automatically recognize a person without causing repulsion at deteciton process. However, the face recognition system has a drawback to show lower perfomance according to illumination variation unlike the other biometric systems using fingerprint and iris. Therefore, this paper proposed a robust face recogntion method against illumination varition by slective fusion technique using both visible and infrared faces based on fuzzy linear disciment analysis(fuzzy-LDA). In the first step, both the visible image and infrared image are divided into four bands using wavelet transform. In the second step, Euclidean distance is calculated at each subband. In the third step, recognition rate is determined at each subband using the Euclidean distance calculated in the second step. And then, weights are determined by considering the recognition rate of each band. Finally, a fusion face recognition is performed and robust recognition results are obtained.

The Recognition and Segmentation of the Road Surface State using Wavelet Image Processing (웨이블릿 영상처리에 의한 도로표면상태 인식 및 분류)

  • Han, Tae-Hwan;Ryu, Seung-Ki;Song, Wonseok;Lee, Seung-Rae
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • 제22권4호
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    • pp.26-34
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    • 2008
  • This study focus on segmentation process that classifies road surfaces into 5 different categories, dry, wet water, icy, and snowy surfaces by analyzing asphalt-paved road images taken in daylight. By using the polarization coefficients, the proportions of horizontally polarized components to vertically polarized components, regions with over 1.3 polarization coefficients are classified as wet surfaces. Except for wet surfaces, the decision process a lies time-frequency analysis to other parts by using the third order wavelet packet transform. In addition, by using the average frequency characteristics of dry and icy surfaces from image templates, decide which is closer to a test image, and finally identify dry and icy surfaces. It is confirmed that the reposed estimation and segmentation of recognition on various images. This can be interpreted as an indication that image-only mad surface condition supervision is probable.

Spike Rejection Method for Improving Altitude Control Performance of Quadrotor UAV Using Ultrasonic Rangefinder (초음파 거리계를 이용하는 쿼드로터 무인항공기의 고도 제어 성능 향상을 위한 스파이크 제거 기법)

  • Kim, Sung-Hoon;Choi, Kyeung-Sik;Hong, Gyo-Young
    • Journal of Advanced Navigation Technology
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    • 제20권3호
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    • pp.196-202
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    • 2016
  • In this paper, a stationary wavelet transform method is proposed for improving the altitude control performance of quadrotor UAV using an ultrasonic rangefinder. A ground tests are conducted using an ultrasonic rangefinder that is much used for vertical takeoff and landing. An ultrasonic rangefinder suffers from signal's spike due to specular reflectance and acoustic noise. The occurred spikes in short time span need to be analyzed at both sides time and frequency domain. It was known that stationary wavelet transform is the transferring solution to the problem occurred by down sampling from DWT also more efficient to remove noise than DWT. The analyzed spikes of the ultrasonic rangefinder using a stationary wavelet transform and experimental results show that it can effectively remove the spikes of the ultrasonic rangefinder.

A Wavelet-based Profile Classification using Support Vector Machine (SVM을 이용한 웨이블릿기반 프로파일분류에 관한 연구)

  • Kim, Seong-Jun
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 한국지능시스템학회 2008년도 춘계학술대회 학술발표회 논문집
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    • pp.3-6
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    • 2008
  • 베어링은 각종 설비에서 활용하는 중요한 기계요소 중 하나이다. 설비고장의 상당수는 베어링의 결함이나 파손에 기인하고 있다. 따라서 베어링에 대한 온라인모니터링기술은 설비의 정지를 예방하고 손실을 줄이는 데 필수적이다. 본 논문은 진동신호를 이용하여 베어링의 상태를 예측하기 위한 온라인모니터링에 대해 연구한다. 프로파일로 주어지는 진동신호는 이산웨이블릿변환을 통해 분석되고, 분해수준별 웨이블릿계수로부터 얻은 통계적 특징 중 유의한 것을 선별하고자 분산분석 (ANOVA)을 이용한다. 선별된 특징벡터는 Support Vector Machine (SVM)의 입력이 되는 데, 본 논문에서는 다중클래스 분류문제를 다루기 위한 계층적 SVM 네트워크를 제안한다.

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Features Extraction for Classifying Parkinson's Disease Based on Gait Analysis (걸음걸이 분석 기반의 파킨슨병 분류를 위한 특징 추출)

  • Lee, Sang-Hong;Lim, Joon-S.;Shin, Dong-Kun
    • Journal of Internet Computing and Services
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    • 제11권6호
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    • pp.13-20
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    • 2010
  • This paper presents a measure to classify healthy persons and Parkinson disease patients from the foot pressure of healthy persons and that of Parkinson disease patients using gait analysis based characteristics extraction and Neural Network with Weighted Fuzzy Membership Functions (NEWFM). To extract the inputs to be used in NEWFM, in the first step, the foot pressure data provided by the PhysioBank and changes in foot pressure over time were used to extract four characteristics respectively. In the second step, wavelet coefficients were extracted from the eight characteristics extracted from the previous stage using the wavelet transform (WT). In the final step, 40 inputs were extracted from the extracted wavelet coefficients using statistical methods including the frequency distribution of signals and the amount of variability in the frequency distribution. NEWFM showed high accuracy in the case of the characteristics obtained using differences between the left foot pressure and the right food pressure and in the case of the characteristics obtained using differences in changes in foot pressure over time when healthy persons and Parkinson disease patients were classified by extracting eight characteristics from foot pressure data. Based on these results, the fact that differences between the left and right foot pressures of Parkinson disease patients who show a characteristic of dragging their feet in gaits were relatively smaller than those of healthy persons could be identified through this experiment.

Analysis and Recognition of Behavioral Response of Selected Insects in Toxic Chemicals for Water Quality Monitoring (수질 모니터링을 위한 유해 물질 유입에 따른 생물체의 행동 반응 분석 및 인식)

  • Kim, Cheol-Ki;Cha, Eui-Young
    • The KIPS Transactions:PartB
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    • 제9B권5호
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    • pp.663-672
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    • 2002
  • In this paper, Using an automatic tracking system, behavior of an aquatic insect, Chironomus sp. (Chironomidae), was observed in semi-natural conditions in response to sub-lethal treament of a carbamate insecticide, carbofuran. The fourth instar larvae were placed in an observation cage $(6cm\times{7cm}\times{2.5cm)}$ at temperature of $18^\circ{C}$ and the light condition of 10 time (light) : 14 time (dark). The tracking system was devised to detect the instant, partial movement of the insect body. Individual movement was traced after the treatment of carbofuran (0.1ppm) for four days 2days : before treatment, 2 days : after treatment). Along with the other irregular behaviors, "ventilation activity", appearing as a shape of "compressed zig-zag", was more frequently observed after the treatment of the insecticide. The activity of the test individuals was also generally depressed after the chemical treatment. In order to detect behavioral changes of the treated specimens, wavelet analysis was implemented to characterize different movement patterns. The extracted parameters based on Discrete Wavelet Transforms (DWT) were subsequently provided to artificial neural networks to be trained to represent different patterns of the movement tracks before and after treatments of the insecticide. This combined model of wavelets and artificial neural networks was able to point out the occurrence of characteristic movement patterns, and could be an alternative tool for automatically detecting presences of toxic chemicals for water quality monitoring. quality monitoring.

Characteristic Analysis of the Tidal Residuals' Mid/Long-period Components Using a Wavelet Method (웨이블릿방법을 이용한 조위편차 성분의 중·장주기 특성 분석)

  • Kang, Ju Whan;Kim, Yang-Seon;Shim, Jae-Seol
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • 제25권4호
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    • pp.200-206
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    • 2013
  • Fourier analysis and a wavelet method were carried out to elucidate the characteristics of tidal residual components in coastal waters. The result of Fourier analysis shows tide-induced and monsoon-induced residuals are conspicuous at the short period and mid period, respectively. The tidal residuals were decomposed by period from 3 hours to 8 months and the characteristics of their components were shown by reconstituting them with short periods less than 24 hours, mid-periods between 1 day and 16 days and long periods longer than 1 month. The tidal residuals in the short period, i.e., tide-induced components, being based on the tidal elevation prediction errors, appear in the West Sea with high tidal ranges and do not have much seasonal fluctuation. Additionally, the period of typhoon induced surge ranges more or less than 12 hours. The mid-period components were clearly generated mainly in the West Sea during the winter and largely affected by monsoon. Accordingly, the pure surge height components were concentrated on the mid-period and had clear features for each coastal waters. The long period components show similar characteristics at all stations and are considered to stem from variations of mean sea levels.

Adaptive Deringing filter's Design and Performance Analysis on Edge Region Classification (윤곽 영역 분류에 기반한 적응형 디링잉 필터의 설계 및 성능 분석)

  • Cho Young;Park Chang-Han;Namkung Jae-Chan
    • Journal of Korea Multimedia Society
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    • 제7권10호
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    • pp.1378-1388
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    • 2004
  • This paper proposes method to improve the image quality degradation that show when reconstructing compressed images at low bit rate by using wavelet transform. The image quality distortion is blocking artifacts and noise in DCT's compression but blocking artifacts of wavelet transform does not appear and ringing artifacts was appeared near the edge. This proposed technique is classified to part which is ringing artifacts of the edge vicinity appears which is not, apply adaptive filter to each region improved image. A edge region which is harsh to the eye is applied by Canny mask and finding strong edge region, search the neighborhood classify the flat region and the texture region, and apply to each region suitable filter, As experiment result, PSNR value of method that is proposed in that low bit rate compression image that ringing artifact appears became low about 0.05db, but 0.023db degree rose strong edge region and nat region's image. Also, showed picture quality improved more than ringing artifacts in nat region when see from subjective viewpoint of human.

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Real-time Recognition System of Facial Expressions Using Principal Component of Gabor-wavelet Features (표정별 가버 웨이블릿 주성분특징을 이용한 실시간 표정 인식 시스템)

  • Yoon, Hyun-Sup;Han, Young-Joon;Hahn, Hern-Soo
    • Journal of the Korean Institute of Intelligent Systems
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    • 제19권6호
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    • pp.821-827
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    • 2009
  • Human emotion can be reflected by their facial expressions. So, it is one of good ways to understand people's emotions by recognizing their facial expressions. General recognition system of facial expressions had selected interesting points, and then only extracted features without analyzing physical meanings. They takes a long time to find interesting points, and it is hard to estimate accurate positions of these feature points. And in order to implement a recognition system of facial expressions on real-time embedded system, it is needed to simplify the algorithm and reduce the using resources. In this paper, we propose a real-time recognition algorithm of facial expressions that project the grid points on an expression space based on Gabor wavelet feature. Facial expression is simply described by feature vectors on the expression space, and is classified by an neural network with its resources dramatically reduced. The proposed system deals 5 expressions: anger, happiness, neutral, sadness, and surprise. In experiment, average execution time is 10.251 ms and recognition rate is measured as 87~93%.

Decomposition of Wave Components in Sea Level Data using Discrete Wavelet Transform (이산형 웨이블릿 변환을 통한 조위 자료 내 파고 성분 분리)

  • Yoo, Younghoon;Lee, Myungjin;Lee, Taewoo;Kim, Soojun;Kim, Hung Soo
    • Journal of Wetlands Research
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    • 제21권4호
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    • pp.365-373
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    • 2019
  • In this study, we investigated the effect of wave height in coastal areas using discrete wavelet transform in Taehwa river basin in Ulsan. Through the decomposition result of tide data using daubechies level 7 wavelet and Curve Fitting Function, we confirmed that detail components of d3 and d4 were semidiurnal and diurnal components and approximation component(a6) was the long period of lunar fortnight constituent. The decomposed tide data in six level was divided into tide component with periodicity and wave component with non-periodicity using autocorrelation function and fourier transform. Finally, we confirmed that the tide component is consisted 66% and wave component is consisted 34%. So, we quantitatively assessed the effect of wave on coastal areas. The result could be used for coastal flood risk management considering the effect of wave.