• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.644-647
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• 1996

In this study the theoretical minimum resolution analysis of an active vision system using laser range finder is performed for surrounding recognition and 3D data acquisition in unknown environment. The laser range finder consists of a slitted laser beam generator, a scanning mechanism, CCD camera, and a signal processing unit. A laser beam from laser source is slitted by a set of cylindrical lenses and the slitted laser beam is emitted up and down and rotates by the scanning mechanism. The image of laser beam reflected on the surface of an object is engraved on the CCD array. In the result, the resolution of range data in laser range finder is depend on distance between lens center of CCD camera and light emitter, view and beam angles, and parameters of CCD camera.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.82-87
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• 1998

In this study, the theoretical resolution analysis of an active vision system using laser range finder is performed for surrounding recognition and 3D data acquisition in unknown environment. In the result, the resolution of range data in laser range finder is depend on the distance between lens center of CCD camera and light emitter, view angle, beam angle, and parameters of CCD camera. The theoretical resolutions of the laser range finders of various types which are based on parameters effected resolution are calculated and experimental results are obtained in real system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.510-514
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• 1994

This paper deals with an application of neural network to camera calibration with wide angle lens and 2-D range finding. Wide angle lens has an advantage of having wide view angles for mobile environment recognition ans robot eye in hand system. But, it has severe radial distortion. Multilayer neural network is used for the calibration of the camera considering lens distortion, and is trained it by error back-propagation method. MLP can map between camera image plane and plane the made by structured light. In experiments, Calibration of camers was executed with calibration chart which was printed by using laser printer with 300 d.p.i. resolution. High distortion lens, COSMICAR 4.2mm, was used to see whether the neural network could effectively calibrate camera distortion. 2-D range of several objects well be measured with laser range finding system composed of camera, frame grabber and laser structured light. The performance of 3-D range finding system was evaluated through experiments and analysis of the results.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.104-112
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• 2019

This study proposed a robust detection algorithm. It detects face more stably with respect to changes in light and rotation forthe identification of a face shape. The proposed algorithm uses face shape asinput information in a single camera environment and divides only face area through preprocessing process. However, it is not easy to accurately recognize the face area that is sensitive to lighting changes and has a large degree of freedom, and the error range is large. In this paper, we separated the background and face area using the brightness difference of the two images to increase the recognition rate. The brightness difference between the two images means the difference between the images taken under the bright light and the images taken under the dark light. After separating only the face region, the face shape is recognized by using the self-organization feature map (SOFM) algorithm. SOFM first selects the first top neuron through the learning process. Second, the highest neuron is renewed by competing again between the highest neuron and neighboring neurons through the competition process. Third, the final top neuron is selected by repeating the learning process and the competition process. In addition, the competition will go through a three-step learning process to ensure that the top neurons are updated well among neurons. By using these SOFM neural network algorithms, we intend to implement a stable and robust real-time face shape recognition system in face shape recognition.

• Proceedings of the KSPS conference
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• 2004.05a
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• pp.231-234
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• 2004

This paper describes an efficient method for improving the noise-robustness in speech recognition in a running car by considering wind noise. In driving car, mainly three kind of noises engine noise, tire noise and wind noise, are severely affect recognition performance. Especially wind noise is an important factor in driving car with window opened. We analyzed wind noise in various driving conditions that are 60, 80, 100 km/h with window fully opened, window half opened. We clarified that the recognition rate is significantly degenerated when the wind noise components in the frequency range above 200 Hz are large. We developed a preprocessing method to improve the noise robustness despite of wind noise. We adaptively changed the cutoff frequency of the front-end high-pass filter from 100 through 200 Hz according to the level of the wind noise components. By this method, the recognition rate is considerably improved for all kind of driving conditions

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.848-855
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• 2016

Face recognition has received a great deal of attention for the wide range of applications in real-world scenario. In this scenario, mismatches (so called heterogeneity) in terms of resolution and illumination between gallery and test face images are inevitable due to the different capturing conditions. In order to deal with the mismatch problem, we propose a local feature learning method using deep canonical correlation analysis (DCCA) for heterogeneous face recognition. By the DCCA, we can effectively reduce the mismatch between the gallery and the test face images. Furthermore, the proposed local feature learned by the DCCA is able to enhance the discriminative power by using facial local structure information. Through the experiments on two different scenarios (i.e., matching near-infrared to visible face images and matching low-resolution to high-resolution face images), we could validate the effectiveness of the proposed method in terms of recognition accuracy using publicly available databases.

• Journal of the Korean Home Economics Association
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• v.31 no.3
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• pp.29-46
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• 1993

The purpose of this study were to investigate the relation between home management ability and family life satisfaction of home makers, and to find out variables which influence them. The data were collected though the questionnaire whose respondent were 408 home makers in Kwang Ju and Kang Reung. The data were analyzed by various statistical method such as Cronbach's coefficient, factor analysis, frequency, percentage, mean, F-test, t-test, Duncan's multiple range test, regression analysis and path analysis. The results were as follow. 1. Home management ability score showed 68.5. Influential variables on home management ability were the level of education (husband and wife), occupation of husband and income as sociodemographic variables, and degree of resourcefulness recognition and of communication as psychological variables. 2. Family life satisfaction score showed 74.6. Influential variables on home management ability were the level of education (husband), occupation of husband and income as sociodemographic variables, and degree of resourcefulness recognition, of communication and of stress recognition as psychological variables. 3. The degree of communication was the highest influential variable to have influence on family life satisfaction. And the degree of resourcefulness recognition, of stress recognition, occupation of husband and wife, level of education(husband), number of children were variables to have directly and/or indirectly influence on family life satisfaction.

• Bulletin of the Korean Chemical Society
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• v.34 no.1
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• pp.159-163
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• 2013

A new Rhodamine B hydrazide hydrazone 1 has been synthesized and investigated as a colorimetric and fluorescent "off-on" sensor for the recognition of $Cu^{2+}$ in $CH_3CN/H_2O$ (1:1, v/v, HEPES 10 mM, pH = 7.0) solution. Sensor 1 displayed highly selective, sensitive and rapid recognition behavior toward $Cu^{2+}$ among a range of biologically and environmentally important metal ions. Sensor 1 bind $Cu^{2+}$ via a 1:1 stoichiometry with an association constant of $1.92{\times}10^6\;M^{-1}$, and the detection limit is evaluated to be $7.96{\times}10^{-8}\;M$. The $Cu^{2+}$ recognition event is reversible and is barely interfered by other coexisting metal ions.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.36 no.4
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• pp.270-274
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• 2010

Introduction: Limited mouth opening is a representative clinical symptom of temporomandibular disorders (TMD) with anterior disc displacement without reduction (ADDWOR). Various treatment methods have been proposed for patients with ADDWOR. This study examined the clinical effectiveness of template therapy for patients with mouth opening difficulty due to the ADDWOR. Material and Methods: A total of 14 patients (female 12, male 2, average age: $29.1{\pm}14.4$), who had been treated in the template clinic, Sooncheonhyang University Bucheon Hospital, from January of 2006 to December of 2008, were enrolled in this study. The subjects were selected according to the following criteria: more than 2 weeks after the onset of locking, mouth opening range <35 mm, and confirmed ADDWOR without a synovial pathology by magnetic resonance imaging (MRI). All patients were treated with the template appliance, instructed to wear it while sleeping and exercise for at least 10 hours per day. The maximum mouth opening (MMO) range and pain recognition scores before and after template therapy were recorded and compared. A paired t-test and Wilcoxon's signed rank test were used for statistical analysis. Results: After the periodical follow up, significant improvement in the opening range was observed in the template treatment group. The average MMO range before treatment was $30.2{\pm}3.5mm$ and the average MMO after treatment and follow up was $47.1{\pm}4.7mm$. The mean amount of mouth opening increment was $16.9{\pm}5.4mm$ (P<0.01) and the pain recognition scores before and after treatment was also improved.(P=0.001) Conclusion: The template appliance proved to be efficient for the treatment of TMD with a closed lock and painful joint due to ADDWOR.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.415-420
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• 1989

This thesis deals with range finding using one camera and laser pointer. Range finding will be used further recognition of the image, that is, range image which allows further segmentation of the scene. In the first step, camera modeling is performed by camera calibration which executes least square fit. Least square fit uses the method of sigular value decomposition. And perspective transform of camera is obtained. Lastly range finding is performed by triangulation principle. The result of this algorithm are displayed.