• Title/Summary/Keyword: Feature Distribution

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A Feature-Based Retrieval Technique for Image Database (특징기반 영상 데이터베이스 검색 기법)

  • Kim, Bong-Gi;Oh, Hae-Seok
    • The Transactions of the Korea Information Processing Society
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    • v.5 no.11
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    • pp.2776-2785
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    • 1998
  • An image retrieval system based on image content is a key issue for building and managing large multimedia database, such as art galleries and museums, trademarks and copyrights, and picture archiving and communication system. Therefore, the interest on the subject of content-based image retrieval has been greatly increased for the last few years. This paper proposes a feature-based image retrieval technique which uses a compound feature vector representing both of color and shape of an image. Color information for the feature vector is obtained using the algebraic moment of each pixel of an image based on the property of regional color distribution. Shape information for the feature vector is obtained using the Improved Moment Invariant(IMI) which reduces the quantity of computation and increases retrieval efficiency. In the preprocessing phase for extracting shape feature, we transform a color image into a gray image. Since we make use of the modified DCT algorithm, it is implemented easily and can extract contour in real time. As an experiment, we have compared our method with previous methods using a database consisting of 150 automobile images, and the results of the experiment have shown that our method has the better performance on retrieval effectiveness.

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Feature Extraction for Protein Pattern Using Fuzzy Integral (퍼지적분을 이용한 단백질패턴에 관한 특징추출)

  • Song, Young-Jun;Kwon, Heak-Bong;Kim, Mi-Hye
    • The Journal of the Korea Contents Association
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    • v.7 no.1
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    • pp.40-47
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    • 2007
  • In the protein macro array image, it is important to find out the feature of the each protein chip. A decision error by the personal sense of sight occurred from long time observation while making an experiment in many protein chip image. So the feature extraction is needed by a simulator. In the case of feature analysis for macro array scan image the efficiency is maximized. In the fluorescence scan image, the response for each cell have been depend on R, G, B distribution of color image. But it is difficult to be classified as one color feature in the case of mixed color image. In this paper, the response color of a protein chip is classified according to the fuzzy integral value with respect to fuzzy measure as the user desired color. The result of the experiment for the macro array fluorescence image with the Scan Array 5000 shows that the proposed method using the fuzzy integral is important fact to be make decision for the ambiguous color.

Object Detection and Classification Using Extended Descriptors for Video Surveillance Applications (비디오 감시 응용에서 확장된 기술자를 이용한 물체 검출과 분류)

  • Islam, Mohammad Khairul;Jahan, Farah;Min, Jae-Hong;Baek, Joong-Hwan
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.4
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    • pp.12-20
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    • 2011
  • In this paper, we propose an efficient object detection and classification algorithm for video surveillance applications. Previous researches mainly concentrated either on object detection or classification using particular type of feature e.g., Scale Invariant Feature Transform (SIFT) or Speeded Up Robust Feature (SURF) etc. In this paper we propose an algorithm that mutually performs object detection and classification. We combinedly use heterogeneous types of features such as texture and color distribution from local patches to increase object detection and classification rates. We perform object detection using spatial clustering on interest points, and use Bag of Words model and Naive Bayes classifier respectively for image representation and classification. Experimental results show that our combined feature is better than the individual local descriptor in object classification rate.

Calculating Cp of Position Tolerance when MMC Applied at Datum and Position Tolerance (데이텀과 위치공차에 최대실체조건이 적용되었을 경우의 위치공차의 Cp)

  • Kim, Jun-Ho;Chang, Sung-Ho
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.40 no.3
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    • pp.1-6
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    • 2017
  • Process capability is well known in quality control literatures. Process capability refers to the uniformity of the process. Obviously, the variability in the process is a measure of the uniformity of output. It is customary to take the 6-sigma spread in the distribution of the product quality characteristic as a measure of process capability. However there is no reference of process capability when maximum material condition is applied to datum and position tolerance in GD&T (Geometric Dimensioning and Tolerancing). If there is no material condition in datum and position tolerance, process capability can be calculated as usual. If there is a material condition in a feature control frame, bonus tolerance is permissible. Bonus tolerance is an additional tolerance for a geometric control. Whenever a geometric tolerance is applied to a feature of size, and it contains an maximum material condition (or least material condition) modifier in the tolerance portion of the feature control frame, a bonus tolerance is permissible. When the maximum material condition modifier is used in the tolerance portion of the feature control frame, it means that the stated tolerance applies when the feature of size is at its maximum material condition. When actual mating size of the feature of size departs from maximum material condition (towards least material condition), an increase in the stated tolerance-equal to the amount of the departure-is permitted. This increase, or extra tolerance, is called the bonus tolerance. Another type of bonus tolerance is datum shift. Datum shift is similar to bonus tolerance. Like bonus tolerance, datum shift is an additional tolerance that is available under certain conditions. Therefore we try to propose how to calculate process capability index of position tolerance when maximum material condition is applied to datum and position tolerance.

A Study on Takenical Development that by BLU Part (BLU 부품 기술개발 연구)

  • Kim, Soo-Yong;Lee, Oh-Keol
    • Proceedings of the KIEE Conference
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    • 2001.07c
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    • pp.1804-1807
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    • 2001
  • By comparing and analyzing the feature, brightness, chromaticity and uniformity of domestic LGPs and Japanese products, early home-manufacturing and stabilization in home-manufacturing are possible. By comparing and analyzing the distribution of brightness as sheets are varied, we can design an ideal sheet composition.

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Visual Comfort Enhancement of Auto-stereoscopic 3D Display using the Characteristic of Disparity Distribution (시차 분포 특성을 이용한 오토스테레오스코픽 3차원 디스플레이 시청 피로도 개선 방법)

  • Kim, Donghyun;Sohn, Kwanghoon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.3
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    • pp.107-113
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    • 2016
  • Visual discomfort is a common problem in three-dimensional videos. Among the methods to overcome visual discomfort presented in current research, disparity adjustment methods provide little guidance in determining the condition for disparity control. We propose a diaprity adjustment based on the characteristics of disparity distribution on visual comfort, where the visual comfort level is used as the adjustment paramter, in parallax barrier type auto-stereoscopic 3D display. In this paper, we use the horizontal image shift method for disparity adjustment to enhance visual comfort. The speeded-up robust feature is used to estimate the disparity distribution of 3D sequences, and the required amount for disparity control is chosen based on the pre-defined characteristics of disparity distribution on visual comfort. To evaluate the performance of the proposed method, we used a 3D equipment. Subjective tests were conducted at the fixed optimal viewing distance. The results show that comfortable videos were generated based on the proposed disparity adjustment method.

Impact of Economic Value in the O2O Distribution Channel on Brand Attractiveness and Performance

  • Seok-Beom, CHOI;Hye-Young, JOO;Hokey, MIN;Qaiser Farooq, DAR;Young-Hyo, AHN
    • Journal of Distribution Science
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    • v.21 no.2
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    • pp.7-20
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    • 2023
  • Purpose: With the unique feature of O2O, consumers are now able to check the profile of the services and products online and then consume them in offline venues or vice versa. This study provides motivation and practical implications about online-to-offline (O2O) distribution channels and investigates the relationship between economic values, service consistency and brand identity attractiveness in the O2O distribution channel. Then identify the impact of brand identity attractiveness on the performance (reputation and reuse intention). Research design, data, and methodology: Structural equation modeling (SEM) has been used to investigate the relationship between economic value and brand identity attractiveness, which affects the reputation and reuse intention of services in O2O. Results: Empirical results show the positive and significant impact of economic value and service consistency on brand identity attractiveness which results the positive and significant impact on performance (reputation and reuse intention) in O2O. Conclusion: In the O2O distribution channel, economic value is an important aspect for the attractive image and brand identity. On the other side, brand identity attractiveness is important for the bright future of O2O services, continuous growth, achieving the distinct goal, keeping good promises with customers, and a better reputation of O2O services in distribution channels.

A tracking of the moving objects using normalized hue distribution in HSI color model

  • Shin Chang Hoon;Lim Kang Mo;Lee Se Yeun;Kim Yoon Ho;Lee Joo shin
    • Proceedings of the IEEK Conference
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    • 2004.08c
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    • pp.823-826
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    • 2004
  • In this paper, A tracking of the moving objects using normalized hue distribution in HSI color model was proposed. Moving objects are detected by using difference image method and integral projection method to background image and objects image only with hue area. Hue information of the detected moving area are normalized by 24 levels from $0^{\circ}$ to $3600^{\circ}A$ distance in between normalized levels with a hue distribution chart of the normalized moving objects is used for the identity distinction feature parameters of the moving objects. To examine proposed method in this paper, image of moving cars are obtained by setting up three cameras at different places every 1 km on outer motorway. The simulation results of identity distinction show that it is possible to distinct the identity a distance in between normalization levels of a hue distribution chart without background.

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A Study on the Location Characteristics and Present Distribution of Facilities in the Community (지역시설의 입지특성 및 분포현황에 관한 연구)

  • Jang, Taek-ju
    • Journal of the Korean Institute of Rural Architecture
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    • v.9 no.3
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    • pp.1-10
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    • 2007
  • This study aims to discuss the location characteristics and present distribution of facilities in the rural community. The purpose of this study is to suggest the basic data of the planning of facilities corresponding to the living sphere in community. The circumstances, location and distribution of the rural area facilities was analyzed through field investigation and interview. lt is necessary for ameliorating the income of inhabitants and the status of living environment to make a general local plan in developing rural area. That will be a solution to tackle the decreasement of population in the rural area. The survey's result is observed different by the feature of rural area, adjacence with near rural center, scale of rural center. So a standard of the various facility's arrangement plan must be established, and it must be enlarged in rural area.

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Improvement of Self Organizing Maps using Gap Statistic and Probability Distribution

  • Jun, Sung-Hae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.8 no.2
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    • pp.116-120
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    • 2008
  • Clustering is a method for unsupervised learning. General clustering tools have been depended on statistical methods and machine learning algorithms. One of the popular clustering algorithms based on machine learning is the self organizing map(SOM). SOM is a neural networks model for clustering. SOM and extended SOM have been used in diverse classification and clustering fields such as data mining. But, SOM has had a problem determining optimal number of clusters. In this paper, we propose an improvement of SOM using gap statistic and probability distribution. The gap statistic was introduced to estimate the number of clusters in a dataset. We use gap statistic for settling the problem of SOM. Also, in our research, weights of feature nodes are updated by probability distribution. After complete updating according to prior and posterior distributions, the weights of SOM have probability distributions for optima clustering. To verify improved performance of our work, we make experiments compared with other learning algorithms using simulation data sets.