• Title/Summary/Keyword: Gaussian Model

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Object-Based Integral Imaging Depth Extraction Using Segmentation (영상 분할을 이용한 객체 기반 집적영상 깊이 추출)

  • Kang, Jin-Mo;Jung, Jae-Hyun;Lee, Byoung-Ho;Park, Jae-Hyeung
    • Korean Journal of Optics and Photonics
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    • v.20 no.2
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    • pp.94-101
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    • 2009
  • A novel method for the reconstruction of 3D shape and texture from elemental images has been proposed. Using this method, we can estimate a full 3D polygonal model of objects with seamless triangulation. But in the triangulation process, all the objects are stitched. This generates phantom surfaces that bridge depth discontinuities between different objects. To solve this problem we need to connect points only within a single object. We adopt a segmentation process to this end. The entire process of the proposed method is as follows. First, the central pixel of each elemental image is computed to extract spatial position of objects by correspondence analysis. Second, the object points of central pixels from neighboring elemental images are projected onto a specific elemental image. Then, the center sub-image is segmented and each object is labeled. We used the normalized cut algorithm for segmentation of the center sub-image. To enhance the speed of segmentation we applied the watershed algorithm before the normalized cut. Using the segmentation results, the subdivision process is applied to pixels only within the same objects. The refined grid is filtered with median and Gaussian filters to improve reconstruction quality. Finally, each vertex is connected and an object-based triangular mesh is formed. We conducted experiments using real objects and verified our proposed method.

A Method of Detecting the Aggressive Driving of Elderly Driver (노인 운전자의 공격적인 운전 상태 검출 기법)

  • Koh, Dong-Woo;Kang, Hang-Bong
    • KIPS Transactions on Software and Data Engineering
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    • v.6 no.11
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    • pp.537-542
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    • 2017
  • Aggressive driving is a major cause of car accidents. Previous studies have mainly analyzed young driver's aggressive driving tendency, yet they were only done through pure clustering or classification technique of machine learning. However, since elderly people have different driving habits due to their fragile physical conditions, it is necessary to develop a new method such as enhancing the characteristics of driving data to properly analyze aggressive driving of elderly drivers. In this study, acceleration data collected from a smartphone of a driving vehicle is analyzed by a newly proposed ECA(Enhanced Clustering method for Acceleration data) technique, coupled with a conventional clustering technique (K-means Clustering, Expectation-maximization algorithm). ECA selects high-intensity data among the data of the cluster group detected through K-means and EM in all of the subjects' data and models the characteristic data through the scaled value. Using this method, the aggressive driving data of all youth and elderly experiment participants were collected, unlike the pure clustering method. We further found that the K-means clustering has higher detection efficiency than EM method. Also, the results of K-means clustering demonstrate that a young driver has a driving strength 1.29 times higher than that of an elderly driver. In conclusion, the proposed method of our research is able to detect aggressive driving maneuvers from data of the elderly having low operating intensity. The proposed method is able to construct a customized safe driving system for the elderly driver. In the future, it will be possible to detect abnormal driving conditions and to use the collected data for early warning to drivers.

A study on the Derivation of GIUH-Clark Model (GIUH-Clark 모형의 유도에 관한 연구)

  • Lee, Byung Woon;Jang, Dae Won;Kim, Hung Soo;Seoh, Byung Ha
    • Proceedings of the Korea Water Resources Association Conference
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    • 2004.05b
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    • pp.731-736
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    • 2004
  • 강우-유출과정의 수문학적 현상을 보다 정확히 분석하고 예측하는 기법으로 강우에 의한 유출의 반응을 나타내는 지체시간, 도달시간 등 수문학적 반응시간을 유역의 지형형태학적 인자들과 연계하는 방법이 많이 이용되고 있다. 이에 본 연구에서는 Clark방법과 지형형태학적 순간단위도(GIUH)를 이용하여 계측유역의 강우-유출반응을 모의하였고, 이를 관측된 값과 비교하여 미계측유역의 적용성 여부를 검토해보았다. 대상 유역의 하상지형인자 및 지형형태학적 특성은 Arc-View를 이용하여 구하였으며, 이를 기존의 문헌자료와 비교해보았다. Clark방법의 매개변수의 결정에 있어서 시간-면적곡선은 HEC-1의 무차원 식을 이용하였고, 도달시간은 Kirpich 공식을 이용하여 구하였으며, 저류상수는 Clark방법에 의해 추정된 순간단위도의 첨두유량이 Horton의 차수비의 함수로 구한 철두유량과 같아지는 값으로 결정하였다. 본 연구는 전적비교를 출구점으로하는 유역면적 $8.5km^2$인 설마천을 대상유역으로 하였으며, 모의된 강우-유출반응과 비교하기 위해 사용된 강우사상은 2002년의 8월 4일과 2002년 10월 6일의 10분 단위 우량이다. Clark방법과 GIUH를 이용하여 모의한 유출곡선과 관측된 유출곡선을 비교해본 결과 첨두유량은 8월의 강우사상 때는 $21\%$크게, 10월의 강우사상 때는 $35\%$작게 나타났다. 첨두시간은 모의된 경우가 각각 10분, 20분 빨리 도달하였다. 또한 이러한 결과는 유역의 도달시긴에 가장 민감하게 반응함을 알 수 있었다. 따라서, 유역의 도달시간 산정에 주의를 요한다면 프랙탈 차원이 유사한 미계측유역의 수문곡선 산정에 있어서 Clark방법과 GIUH를 이용하는 방법도 유용하다고 사료된다. 주는 각 수문인자 중 강우시간분포와 유효우량 산정방법 그리고 유출모형에 대해 자자 검토하였으며, 최종적으로 면적에 따른 임계지속기간과 유출량의 변화를 검토해 보았다.이를 각각의 경우의 해석해 결과와 비교${\cdot}$분석하였다. 후방추적 퍼프모형은 전방추적 퍼프모형에 비하여 사용된 퍼프수와 관계없이 작은 오차를 발생하였으며, 전체적으로 퍼프 모형이 입자모형보다는 훨씬 적은 수의 계산을 통해서도 작은 오차를 나타낼 수 있다는 것을 알 수 있었다. 그러나 Gaussian 분포를 갖는 퍼프모형은 전단흐름에서의 긴 유선형 농도분포를 모의할 수 없었고, 이에 관한 오차는 전단계수가 증가함에 따라 비선형적으로 증가하였다. 향후, 보다 다양한 흐름영역에서 장${\cdot}$단점 분석 및 오차해석을 수행한 후에 각각의 Lagrangian 모형의 장점만을 갖는 모형결합 방법을 제시할 수 있을 것으로 판단된다.mm/$m^{2}$로 감소한 소견을 보였다. 승모판 성형술은 전 승모판엽 탈출증이 있는 두 환아에서 동시에 시행하였다. 수술 후 1년 내 시행한 심초음파에서 모든 환아에서 단지 경등도 이하의 승모판 폐쇄 부전 소견을 보였다. 수술 후 조기 사망은 없었으며, 합병증으로는 유미흉이 한 명에서 있었다. 술 후 10개월째 허혈성 확장성 심근증이 호전되지 않아 Dor 술식을 시행한 후 사망한 예를 제외한 나머지 6명은 특이 증상 없이 정상 생활 중이다 결론: 좌관상동맥 페동맥이상 기시증은 드물기는 하나, 영유아기에 심근경색 및 허혈성 심근증 또는 선천성 승모판 폐쇄 부전등을 초래하는 심각한 선천성 심질환이다. 그러나 진단 즉시 직접 좌관상동맥-대동맥 이식술로 수술적 교정을 해줌으로써 좋은 성적을 기대할 수 있음을 보여주었다.특히 교사들이 중요하

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Algorithms for Indexing and Integrating MPEG-7 Visual Descriptors (MPEG-7 시각 정보 기술자의 인덱싱 및 결합 알고리즘)

  • Song, Chi-Ill;Nang, Jong-Ho
    • Journal of KIISE:Software and Applications
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    • v.34 no.1
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    • pp.1-10
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    • 2007
  • This paper proposes a new indexing mechanism for MPEG-7 visual descriptors, especially Dominant Color and Contour Shape descriptors, that guarantees an efficient similarity search for the multimedia database whose visual meta-data are represented with MPEG-7. Since the similarity metric used in the Dominant Color descriptor is based on Gaussian mixture model, the descriptor itself could be transform into a color histogram in which the distribution of the color values follows the Gauss distribution. Then, the transformed Dominant Color descriptor (i.e., the color histogram) is indexed in the proposed indexing mechanism. For the indexing of Contour Shape descriptor, we have used a two-pass algorithm. That is, in the first pass, since the similarity of two shapes could be roughly measured with the global parameters such as eccentricity and circularity used in Contour shape descriptor, the dissimilar image objects could be excluded with these global parameters first. Then, the similarities between the query and remaining image objects are measured with the peak parameters of Contour Shape descriptor. This two-pass approach helps to reduce the computational resources to measure the similarity of image objects using Contour Shape descriptor. This paper also proposes two integration schemes of visual descriptors for an efficient retrieval of multimedia database. The one is to use the weight of descriptor as a yardstick to determine the number of selected similar image objects with respect to that descriptor, and the other is to use the weight as the degree of importance of the descriptor in the global similarity measurement. Experimental results show that the proposed indexing and integration schemes produce a remarkable speed-up comparing to the exact similarity search, although there are some losses in the accuracy because of the approximated computation in indexing. The proposed schemes could be used to build a multimedia database represented in MPEG-7 that guarantees an efficient retrieval.

The Abnormality of Posterior Default Mode Network in Medication-Naïve Attention-Deficit Hyperactivity Disorder Children : Resting State fMRI Study (약물 복용력이 없는 주의력결핍 과잉행동장애 아동에서의 뒤쪽 내정상태회로 이상 : 휴식상태 기능적 뇌자기공명영상 연구)

  • Choi, Jee-Wook;Go, Hyo-Jin;Woo, Young-Sup;Song, Seung-Hoon;Yang, Po-Song;Jeong, Bum-Seok
    • Journal of the Korean Academy of Child and Adolescent Psychiatry
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    • v.23 no.2
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    • pp.57-62
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    • 2012
  • Objectives : Characteristic symptoms, including hyperactivity and easy distractibility, in children with attention-deficit hyperactivity disorder (ADHD) suggest that their brain status, even at rest, might differ from that of healthy children. This study was conducted in order to determine whether resting state brain activity is compromised in medication-naive children with ADHD. Methods : Twenty medication-naive children with ADHD (mean age $10.3{\pm}2.5$) and 28 age- and gender-matched healthy volunteers (mean age $10.3{\pm}2.0$) underwent measurements for resting state brain activity using functional magnetic resonance imaging (fMRI). Among resting state related-independent components (RSICs) extracted from fMRI data using independent component analysis, a significant difference in RSICs was observed between groups, using a mixed Gaussian/gamma model. Results : Except for IQ, which was higher in the healthy control group, no demographic difference was observed between the two groups (p<.001). Significantly less activation of one RSIC, which includes the bilateral precuneus/posterior cingulate cortex, occipito-temporal junction, and anterior cingulate cortex, was observed in the ADHD group, compared with the control group (p<.05). Conclusion : An abnormal RSIC, posterior default mode network (DMN), was observed in the medication-naive ADHD group. Results of our study suggest that abnormality of posterior DMN is one of the main pathophysiologies of ADHD.

An Adaptive Data Compression Algorithm for Video Data (사진데이타를 위한 한 Adaptive Data Compression 방법)

  • 김재균
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.12 no.2
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    • pp.1-10
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    • 1975
  • This paper presents an adaptive data compression algorithm for video data. The coling complexity due to the high correlation in the given data sequence is alleviated by coding the difference data, sequence rather than the data sequence itself. The adaptation to the nonstationary statistics of the data is confined within a code set, which consists of two constant length cades and six modified Shannon.Fano codes. lt is assumed that the probability distributions of tile difference data sequence and of the data entropy are Laplacian and Gaussion, respectively. The adaptive coding performance is compared for two code selection criteria: entropy and $P_r$[difference value=0]=$P_0$. It is shown that data compression ratio 2 : 1 is achievable with the adaptive coding. The gain by the adaptive coding over the fixed coding is shown to be about 10% in compression ratio and 15% in code efficiency. In addition, $P_0$ is found to he not only a convenient criterion for code selection, but also such efficient a parameter as to perform almost like entropy.

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Segmentation Method of Overlapped nuclei in FISH Image (FISH 세포영상에서의 군집세포 분할 기법)

  • Jeong, Mi-Ra;Ko, Byoung-Chul;Nam, Jae-Yeal
    • The KIPS Transactions:PartB
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    • v.16B no.2
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    • pp.131-140
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    • 2009
  • This paper presents a new algorithm to the segmentation of the FISH images. First, for segmentation of the cell nuclei from background, a threshold is estimated by using the gaussian mixture model and maximizing the likelihood function of gray value of cell images. After nuclei segmentation, overlapped nuclei and isolated nuclei need to be classified for exact nuclei analysis. For nuclei classification, this paper extracted the morphological features of the nuclei such as compactness, smoothness and moments from training data. Three probability density functions are generated from these features and they are applied to the proposed Bayesian networks as evidences. After nuclei classification, segmenting of overlapped nuclei into isolated nuclei is necessary. This paper first performs intensity gradient transform and watershed algorithm to segment overlapped nuclei. Then proposed stepwise merging strategy is applied to merge several fragments in major nucleus. The experimental results using FISH images show that our system can indeed improve segmentation performance compared to previous researches, since we performed nuclei classification before separating overlapped nuclei.

Development of the Algorithm for Traffic Accident Auto-Detection in Signalized Intersection (신호교차로 내 실시간 교통사고 자동검지 알고리즘 개발)

  • O, Ju-Taek;Im, Jae-Geuk;Hwang, Bo-Hui
    • Journal of Korean Society of Transportation
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    • v.27 no.5
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    • pp.97-111
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    • 2009
  • Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a signal intersection and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, we intend to present a technology capable of overcoming problems in which advanced existing technologies exhibited limitations in handling real-time due to large data capacity such as object separation of vehicles and tracking, which pose difficulties due to environmental diversities and changes at a signal intersection with complex traffic situations, as pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian complex model analytical method which has been considered the best among well-known environmental obstacle reduction methods. To prove that the technology developed by this research has performance advantage over existing automatic traffic accident recording systems, a test was performed by entering image data from an actually operating crossroad online in real-time. The test results were compared with the performance of other existing technologies.

A Study on the Emission and Dispersion of Particulate Matter from a Cement Plant (한 시멘트공장의 분진발생과 대기확산에 관한 조사연구)

  • Chang, Man-Ik;Chung, Yong;Kwon, Sook-Pyo
    • Journal of Preventive Medicine and Public Health
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    • v.16 no.1
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    • pp.67-77
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    • 1983
  • To investigate the an air pollution by particulate matter and its dispersion, a cement plant produceing portland cement 600,000 ton/year and its vicinity were surveyed from Obtober, 1980 to April, 1983. The survey was mainly focused on main stack emmission rate of the cement plant and particle size distribution in the dust, dustfall and total suspended particulate concentration in the area by month and distance from the stack. The results of the study were as follows; 1. The main stack emission rate was surveyed before and after the spray tower was additionally installed to the original E.P bag filter. Before the spray tower installed, the main stack emission rate was higher ($0.64g/Nm^3$) than the emission standard of Korean Environmental Preservation Law's ($0.59g/Nm^3$, amended to $0.4g/Nm^3$ on April 1983), but after the spray tower was installed, its main stack emission rate was markedly decreased to the standard ($0.43g/Nm^3$). 2. $2{\sim}3{\mu}m$ of the particle size was the largest portion (20.8%) of the dust particulate from the main stack and 50% of the frequency distribution was $1.5{\mu}m$ of the size. Most particle size was below $10{\mu}m$. 3. The spray tower reduced the dustfall to $37.81{\sim}9.76\;ton/km^2/month$ while dustfall appeared at $45.29-15.45ton/km^2/month$, in the vicinity of plant before spray tower installed 4. Mean concentrations of total suspended particulate for 24 hours of the various stations were determined in $20.6-200.0{\mu}g/m^3$, 3 stations of tham were higher than the value of Harry and William's arthmetic average standard $130{\mu}g/m^3$. 5. Linear regression between dustfall [X] and total suspended particulate[Y] concentration was an equation, Y=4.024X+11.479.[r=0.91] 6. During the whole seasons in the opposite area 100m apart from the omission source the prevailing wind direction was with estimated more than $30ton/km^2/month$, and the concentration of total suspended particulate for 24 hours averaging time was more than $140{\mu}g/m^3$ in the same area and direction. 7. Assuming the wind direction were constant through the day dustfalls for a day were estimated at $13.40ton/km^2/day,\;10.79ton/km^2/day$ and $4.55ton/km^2/day$ at various distances of 100m, 500m and 1,500m from the emission source respectively. 8. In the simutalion of dustfall and suspended dust by area, Gaussian dispersion model modified by size distribution of particulate matter was not applicated since the emission of dust were from multi sources other them stack. From the above results, it could be applied that the dispersion of dust from the cement plant is estimated and regulated for the purpose of environmental protection.

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Extensions of X-means with Efficient Learning the Number of Clusters (X-means 확장을 통한 효율적인 집단 개수의 결정)

  • Heo, Gyeong-Yong;Woo, Young-Woon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.4
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    • pp.772-780
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    • 2008
  • K-means is one of the simplest unsupervised learning algorithms that solve the clustering problem. However K-means suffers the basic shortcoming: the number of clusters k has to be known in advance. In this paper, we propose extensions of X-means, which can estimate the number of clusters using Bayesian information criterion(BIC). We introduce two different versions of algorithm: modified X-means(MX-means) and generalized X-means(GX-means), which employ one full covariance matrix for one cluster and so can estimate the number of clusters efficiently without severe over-fitting which X-means suffers due to its spherical cluster assumption. The algorithms start with one cluster and try to split a cluster iteratively to maximize the BIC score. The former uses K-means algorithm to find a set of optimal clusters with current k, which makes it simple and fast. However it generates wrongly estimated centers when the clusters are overlapped. The latter uses EM algorithm to estimate the parameters and generates more stable clusters even when the clusters are overlapped. Experiments with synthetic data show that the purposed methods can provide a robust estimate of the number of clusters and cluster parameters compared to other existing top-down algorithms.