• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.473-480
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• 2007

Feature tracking in video frame sequences has suffered from the instability and the frequent failure of feature matching between two successive frames. In this paper, we propose a robust 2D feature tracking method that is stable to long video sequences. To improve the stability of feature tracking, we predict the spatial movement in the current image frame using the state variables. The predicted current movement is used for the initialization of the search window. By computing the feature similarities in the search window, we refine the current feature positions. Then, the current feature states are updated. This tracking process is repeated for each input frame. To reduce false matches, the outlier rejection stage is also introduced. Experimental results from real video sequences showed that the proposed method performs stable feature tracking for long frame sequences.

• Korean Journal of Optics and Photonics
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• v.19 no.2
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• pp.122-126
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• 2008

Dual backlight unit incorporating a single light source integrated with a beam splitting reflector was demonstrated, providing a surface light beam for both the keypad and the display section simultaneously. The reflector was realized by aligning a groove substrate with a matching cover, and a light guiding module comprising a stack of light guide panels and prism/diffuser sheets was attached to both sides of the reflector. A light emanating from the light source-placed in the middle of the substrate-undergoes a series of reflections through the reflector to reach the input of the light guiding module. Then it is transformed into a surface light beam, which is used to irradiate the keypad and display sections simultaneously. As for the accomplished dual surface light sources, the measured average luminance and the spatial luminance uniformity were respectively about $420\;cd/m^2$ and 69% for the keypad section, and $640\;cd/m^2$ and 79% for the display section.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1405-1408
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• 2005

An embedded system has been applied to many fields including households and industrial sites. In the past, user interface products with simple functions were commercialized .but now user demands are increasing and the system has more various applicable fields due to a high penetration rate of the Internet. Therefore, the demand for embedded system is tend to rise In this paper, we Implementation of an embedded system for image tracking. This system is used a fixed IP for the reliable server operation on TCP/IP networks. A real time broadcasting of video image on the internet was developed by using an USB camera on the embedded Linux system. The digital camera is connected at the USB host port of the embedded board. all input images from the video camera is continuously stored as a compressed JPEG file in a directory at the Linux web-server. And each frame image data from web camera is compared for measurement of displacement Vector. That used Block matching algorithm and edge detection algorithm for past speed. And the displacement vector is used at pan/tilt motor control through RS232 serial cable. The embedded board utilized the S3C2410 MPU Which used the ARM 920T core form Samsung. The operating system was ported to embedded Linux kernel and mounted of root file system. And the stored images are sent to the client PC through the web browser. It used the network function of Linux and it developed a program with protocol of the TCP/IP.

• Journal of the Korea Society of Computer and Information
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• v.19 no.7
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• pp.17-25
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• 2014

In the devices that leave video records, it is an important issue to distinguish whether the input image is a real object or a photo when securing an identifying image. Using a single image and sensor, which is a simple way to distinguish the target from distance measurement has many weaknesses. Thus, this paper proposes a way to distinguish a simple photo and a real object by using stereo images. It is not only measures the distance to the target, but also checks a three-dimensional effect by making the depth map of the face area. They take pictures of the photos and the real faces, and the measured value of the depth map is applied to the learning algorithm. Exactly through iterative learning to distinguish between the real faces and the photos looked for patterns. The usefulness of the proposed algorithm was verified experimentally.

• Journal of Digital Convergence
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• v.12 no.7
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• pp.239-245
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• 2014

In this paper, a weighted value wrinkle detection method is suggested based on the analysis on the entire facial features such as face contour, face size, eyes and ears. Firstly, the main facial elements are detected with AAM method entirely from the input screen images. Such elements are mainly composed of shape-based and appearance methods. These are used for learning the facial model and for matching the face from new screen images based on the learned models. Secondly, the face and background are separated in the screen image. Four points with the biggest possibilities for wrinkling are selected from the face and high wrinkle weighted values are assigned to them. Finally, the wrinkles are detected by applying Canny edge algorithm for the interested points of weighted value. The suggested algorithm adopts various screen images for experiment. The experiments display the excellent results of face and wrinkle detection in the most of the screen images.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.1
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• pp.23-28
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• 2016

In this paper, a Multi-Band Ku-band down converter was designed for reception of multi-band digital satellite broadcasting. The Multi-band low-nose down converter was designed to form four local oscillator frequencies (9.75, 10, 10.75 and 11.3GHz) representing a low phase noise due to VCO-PLL with respect to input signals of 10.7 to 12.75GHz and 3-stage low noise amplifier circuit by broadband noise matching, and to select an one band of intermediate frequency (IF) channels by digital control. The developed low-noise downconverter exhibited the full conversion gain of 64dB, and the noise figure of low-noise amplifier was 0.7dB, the P1dB of output signal 15dBm, and the phase noise -73dBc@100Hz at the band 1 carrier frequency of 9.75GHz. The low noise block downconverter (LNB) for receiving four-band digital satellite broadcasting designed in this paper can be used for satellite broadcasting of vessels navigating international waters.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.553-559
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• 2004

In todays security industry, personal identification is also based on biometric. Biometric identification is performed basing on the measurement and comparison of physiological and behavioral characteristics, Biometric for recognition includes voice dynamics, signature dynamics, hand geometry, fingerprint, iris, etc. Iris can serve as a kind of living passport or living password. Iris recognition system is the one of the most reliable biometrics recognition system. This is applied to client/server system such as the electronic commerce and electronic banking from stand-alone system or networks, ATMs, etc. A new algorithm using nonlinear function in recognition process is proposed in this paper. An algorithm is proposed to determine the localized iris from the iris image received from iris input camera in client. For the first step, the algorithm determines the center of pupil. For the second step, the algorithm determines the outer boundary of the iris and the pupillary boundary. The localized iris area is transform into polar coordinates. After performing three times Wavelet transformation, normalization was done using sigmoid function. The converting binary process performs normalized value of pixel from 0 to 255 to be binary value, and then the converting binary process is compare pairs of two adjacent pixels. The binary code of the iris is transmitted to the by server. the network. In the server, the comparing process compares the binary value of presented iris to the reference value in the University database. Process of recognition or rejection is dependent on the value of Hamming Distance. After matching the binary value of presented iris with the database stored in the server, the result is transmitted to the client.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.506-512
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• 2000

In this paper, we propose a Fuzzy Classifier System(FCS) makes the classifier system be able to carry out the mapping from continuous inputs to outputs. The FCS is based on the fuzzy controller system combined with machine learning. Therefore the antecedent and consequent of a classifier in FCS are the same as those of a fuzzy rule. In this paper, the FCS modifies input message to fuzzified message and stores those in the message list. The FCS constructs rule-base through matching between messages of message list and classifiers of fuzzy classifier list. The FCS verifies the effectiveness of classifiers using Bucket Brigade algorithm. Also the FCS employs the Genetic Algorithms to generate new rules and modifY rules when performance of the system needs to be improved. Then the FCS finds the set of the effective rules. We will verifY the effectiveness of the poposed FCS by applying it to Autonomous Mobile Robot avoiding the obstacle and reaching the goal.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.181-185
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• 2017

In this paper, for Broadband Wireles LAN dual-band antenna was designed to satisfy the bandwidth of 2.32GHz and 5.79GHz. the substrate of proposed microstrip antenna is FR-4(er=4.3) and $34mm{\times}50mm{\times}1.5mm$ size and thickness t=0.035mm, and the simulation was used for CST Microwave Studio 2014. input return loss compared -10dB less than operates at and when gain 2.32GHz -19.321dB, 5.79GHz showed the results of -13.033dB. It increased impedance matching, minimized interference between adjacent frequencies, simplified small manufacturing methods, and demonstrated the characteristics of non-directional properties. Thus the proposed antenna satisfied the -10 dB impedancebandwidth requirement while simultaneously covering the Broadband Wireless LAN.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.367-370
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• 2015

This paper proposes an improve method of the detection performance of traffic lights for autonomous driving cars. Earlier detection methods used to adopt color thresholding, template matching and based learning maching methods, but its have some problems such as recognition rate decreasing, slow processing time. The proposed method uses both detection mask and morphological preprocessing. Firstly, input color images are converted to YCbCr image in order to strengthen its illumination, and horizontal edge components are extracted in the Y Channel. Secondly, the region of interest is detected according to morphological characteristics of the traffic lights. Finally, the traffic signal is detected based on color distributions. The proposed method showed that the detection rate and processing time improved rather than the conventional algorithm about some surrounding environments.