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A Study on Implementing Kinect-Based Control for LCD Display Contents (LCD Display 설비 Contents의 Kinect기반 동작제어 기술 구현에 관한 연구)

  • Rho, Jungkyu
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.63 no.4
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    • pp.565-569
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    • 2014
  • Recently, various kinds of new computer controlled devices have been introduced in a wide range of areas, and convenient user interfaces for controlling the devices are strongly needed. To implement natural user interfaces(NUIs) on top of the devices, new technologies like a touch screen, Wii Remote, wearable interfaces, and Microsoft Kinect were presented. This paper presents a natural and intuitive gesture-based model for controlling contents of LCD display. Microsoft Kinect sensor and its SDK are used to recognize human gestures, and the gestures are interpreted into corresponding commands to be executed. A command dispatch model is also proposed in order to handle the commands more naturally. I expect the proposed interface can be used in various fields, including display contents control.

Vision-Based Roadway Sign Recognition

  • Jiang, Gang-Yi;Park, Tae-Young;Hong, Suk-Kyo
    • Transactions on Control, Automation and Systems Engineering
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    • v.2 no.1
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    • pp.47-55
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    • 2000
  • In this paper, a vision-based roadway detection algorithm for an automated vehicle control system, based on roadway sign information on roads, is proposed. First, in order to detect roadway signs, the color scene image is enhanced under hue-invariance. Fuzzy logic is employed to simplify the enhanced color image into a binary image and the binary image is morphologically filtered. Then, an effective algorithm of locating signs based on binary rank order transform (BROT) is utilized to extract signs from the image. This algorithm performs better than those previously presented. Finally, the inner shapes of roadway signs with curving roadway direction information are recognized by neural networks. Experimental results show that the new detection algorithm is simple and robust, and performs well on real sign detection. The results also show that the neural networks used can exactly recognize the inner shapes of signs even for very noisy shapes.

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A Study on Preprocessing Improvement Method for Face Recognition

  • Lim, Yang-Koo;Chae, Duck-Jae;Rhee, Sang-Bum
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1782-1787
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    • 2003
  • A face recognition is currently the field which many research have been processed actively. But many problems must be solved the previous problem. First, We must recognize the face of the object taking a location various lighting change and change of the camera into account. In this paper, we proposed that new method to find feature within fast and correct computation time after scanning PC camera and ID card picture. It converted RGB color space to YUV. A face skin color extracts which equalize a histogram of Y ingredient without the Luminance. After, the method use V' ingredient which transforms V ingredient of YUV and then find the face feature. The result of the experiment shows getting correct input face image from ID Card picture and camera.

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Negative Selection Algorithm for DNA Pattern Classification

  • Lee, Dong-Wook;Sim, Kwee-Bo
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.190-195
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    • 2004
  • We propose a pattern classification algorithm using self-nonself discrimination principle of immune cells and apply it to DNA pattern classification problem. Pattern classification problem in bioinformatics is very important and frequent one. In this paper, we propose a classification algorithm based on the negative selection of the immune system to classify DNA patterns. The negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes ${\eta}$ groups of antigenic receptor for ${\eta}$ different patterns, these receptor groups can classify into ${\eta}$ patterns. We propose a pattern classification algorithm based on the negative selection in nucleotide base level and amino acid level. Also to show the validity of our algorithm, experimental results of RNA group classification are presented.

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A Study on CRM Using Knowledge of Customer in Korean Financial Institutions (고객의 지식을 활용한 금융기관의 CRM에 관한 연구)

  • Kwon Kum-Tack
    • Management & Information Systems Review
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    • v.12
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    • pp.17-35
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    • 2003
  • In the customer-centered era, financial institutions have understood the importance of Customer Relationship Management(CRM), and heavily invested into building the required technology infrastructure more than ever. In a competitive environment that are changing fast, knowledge management is necessary. To know customers' needs and desire, we have to approach their environment and mind, and the method by estimating in terms of supposing or imitating. Applying customers' knowledge is effective and will come up with a stepping-stone to get rid of threatening factors by having competitiveness in a competitive environment and extending and changing the corporation. This purpose, the study has identified knowledge-oriented infra that corporations know and customer relations by conducting a poll of local corporations and have presented motives that can effectively carry out knowledge-based customer relations. To gain competitive advantage, these Institutions need to understand their customers' potential value to find out more and to recognize the significant changes of customer. Then the CRM implementation will help Financial Institutions move to more of a sales culture away from product and closer to the customer.

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Gesture Recognition using Training-effect on image sequences (연속 영상에서 학습 효과를 이용한 제스처 인식)

  • 이현주;이칠우
    • Proceedings of the IEEK Conference
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    • 2000.06d
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    • pp.222-225
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    • 2000
  • Human frequently communicate non-linguistic information with gesture. So, we must develop efficient and fast gesture recognition algorithms for more natural human-computer interaction. However, it is difficult to recognize gesture automatically because human's body is three dimensional object with very complex structure. In this paper, we suggest a method which is able to detect key frames and frame changes, and to classify image sequence into some gesture groups. Gesture is classifiable according to moving part of body. First, we detect some frames that motion areas are changed abruptly and save those frames as key frames, and then use the frames to classify sequences. We symbolize each image of classified sequence using Principal Component Analysis(PCA) and clustering algorithm since it is better to use fewer components for representation of gestures. Symbols are used as the input symbols for the Hidden Markov Model(HMM) and recognized as a gesture with probability calculation.

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Implementation of Real-time Virtual Touch Recognition System in Embedded System (임베디드 환경에서 실시간 가상 터치 인식 시스템의 구현)

  • Kwon, Soon-Kak;Lee, Dong-Seok
    • Journal of Korea Multimedia Society
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    • v.19 no.10
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    • pp.1759-1766
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    • 2016
  • We can implement the virtual touch recognition system by mounting the virtual touch algorithm into an embedded device connected to a depth camera. Since the computing performance is limited in embedded system, the real-time processing of recognizing the virtual touch is difficult when the resolution of the depth image is large. In order to resolve the problem, this paper improves the algorithms of binarization and labeling that occupy a lot of time in all processing of virtual touch recognition. It processes the binarization and labeling in only necessary regions rather than all of the picture. By appling the proposed algorithm, the system can recognize the virtual touch in real-time as about 31ms per a frame in the depth image that has 640×480 resolution.

The vectorization and recognition of circuit symbols for electronic circuit drawing management (전자회로 도면관리를 위한 벡터화와 회로 기호의 인식)

  • 백영묵;석종원;진성일;황찬식
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.3
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    • pp.176-185
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    • 1996
  • Transformin the huge size of drawings into a suitable format for CAD system and recognizng the contents of drawings are the major concerans in the automated analysis of engineering drawings. This paper proposes some methods for text/graphics separation, symbol extraction, vectorization and symbol recognition with the object of applying them to electronic cirucit drawings. We use MBR (Minimum bounding rectangle) and size of isolated region on the drawings for separating text and graphic regions. Characteristics parameters such as the number of pixels, the length of circular constant and the degree of round shape are used for extracting loop symbols and geometric structures for non-loop symbols. To recognize symbols, nearest netighbor between FD (foruier descriptor) of extractd symbols and these of classification reference symbols is used. Experimental results show that the proposed method can generate compact vector representation of extracted symbols and perform the scale change and rotation of extracted symbol using symbol vectorization. Also we achieve an efficient searching of circuit drawings.

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A Study of the Obstacle Avoidance for a Quadruped Walking Robot Using Genetic and Fuzzy Algorithm

  • Lee, Bo-Hee;Kong, Jung-Shik;Kim, Jin-Geol
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.228-231
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    • 2003
  • This paper presents the leg trajectory generation for the quadruped robot with genetic-fuzzy algorithm. To have the nobility even at uneven terrain, a robot is able to recognize obstacles, and generates moving path of body that can avoid obstacles. This robot should have its own avoidance algorithm against obstacles, forwarding to target without collision. During walking period, n robot recognizes obstacle from external environment with a PSD and some interface, and this obstacle information is converted into proper the body rotation angle by fuzzy inference engine. After this process, we can infer the walking direction and walking distance of body, and finally can generate the optimal Beg trajectory using genetic algorithm. All these methods are verified with PC simulation program, and implemented to SERO-V robot.

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A Study on Korean Jacket Style Expressed in Modern Fashion (현대 패션에 표현된 저고리 스타일 연구)

  • Lee, Hyun-Joo;Chae, Keum-Seok
    • Journal of the Korean Society of Clothing and Textiles
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    • v.36 no.2
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    • pp.165-178
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    • 2012
  • This study researches the form of the Korean jacket point through relics from the Three Kingdoms period that have the traditional Korean style and grace of the Goryeo period as well as the form of the modern Korean jacket starting point. Several conclusions can be drawn from the Korean Image of the Korean jacket that can be classified into types expressed in the jacket style of modern fashion. Therefore, we will analyze traditional elements of Korean beauty through the "Korean image" on how to express it in modern fashion. The purpose of this study is to understand modern design creation and Korean culture. It is important to begin the world through the application of traditional elements to recognize Korean beauty as well as to utilize historical dress based on function and popularity to continue the effort.