• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.12
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• pp.55-62
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• 1998

Matching two images is an essential step for many computer vision applications. A new approach to the scale and rotation invariant scene matching, using linear features, is presented. Scene or model images are described by a set of linear features approximating edge information, which can be obtained by the conventional edge detection, thinning, and piecewise linear approximation. A set of candidate parameters are hypothesized by mapping the angular difference and a new distance measure to the Hough space and by detecting maximally consistent points. These hypotheses are verified by a fast linear feature matching algorithm composed of a single-step relaxation and a Hough technique. The proposed method is shown to be much faster than the conventional one where the relaxation process is repeated until convergence, while providing matching performance robust to the random alteration of the linear features, without a priori information on the geometrical transformation parameters.

• The Journal of Sustainable Design and Educational Environment Research
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• v.16 no.3
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• pp.18-26
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• 2017

In order to realize the empathy of the local education community, the education local government should establish the brand design properly in accordance with the enterprise and the large-scale administrative agency and actively use it in the public design strategy and publicity strategy. And the identity and role of education local government that are differentiated from each other can be well communicated and help to achieve the vision. However, the development and utilization of brand design in the provincial education local government is sluggish. In this context, research on urban brand has been carried out variously, but there is no comprehensive analysis on change of education local government brand. The purpose of this research is to analyze the current characteristics of brand design in education local government in order to enhance the image of education direction and to enhance the brand value of education local government.

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.439-448
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• 2020

In this paper, we propose a modified optimization algorithm for point cloud matching of multi-view RGB-D cameras. In general, in the computer vision field, it is very important to accurately estimate the position of the camera. The 3D model generation methods proposed in the previous research require a large number of cameras or expensive 3D cameras. Also, the methods of obtaining the external parameters of the camera through the 2D image have a large error. In this paper, we propose a matching technique for generating a 3D point cloud and mesh model that can provide omnidirectional free viewpoint using 8 low-cost RGB-D cameras. We propose a method that uses a depth map-based function optimization method with RGB images and obtains coordinate transformation parameters that can generate a high-quality 3D model without obtaining initial parameters.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.415-419
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• 2008

Detecting and correcting defects on LCD glasses early in the manufacturing process becomes important for panel makers to reduce the manufacturing costs and to improve productivity. Many attempts have been made and were successfully applied to detect and identify simple defects such as scratches, dents, and foreign objects on glasses. However, it is still difficult to robustly detect low-contrast defect region, called Mura or blemish area on glasses. Typically, these defect areas are roughly defined as relatively large, several millimeters of diameter, and relatively dark and/or bright region of low Signal-to-Noise Ratio (SNR) against background of low-frequency signal. The aim of this article is to present a robust algorithm to segment these blemish defects. Early 90's, a highly robust estimator, known as the Model-Fitting (MF) estimator was developed by X. Zhuang et. al. and have been successfully used in many computer vision application. Compared to the conventional Least-Square (LS) estimator the MF estimator can successfully estimate model parameters from a dataset of contaminated Gaussian mixture. Such a noise model is defined as a regular white Gaussian noise model with probability $1-\varepsilon$ plus an outlier process with probability $varepsilon$. In the sense of robust estimation, the blemish defect in images can be considered as being a group of outliers in the process of estimating image background model parameters. The algorithm developed in this paper uses a modified MF estimator to robustly estimate the background model and as a by-product to segment the blemish defects, the outliers.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.33-44
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• 2010

This paper propose the structure of real-time face detection hardware architecture for robot vision processing applications. The proposed architecture is robust against illumination changes and operates at no less than 60 frames per second. It uses Modified Census Transform to obtain face characteristics robust against illumination changes. And the AdaBoost algorithm is adopted to learn and generate the characteristics of the face data, and finally detected the face using this data. This paper describes the face detection hardware structure composed of Memory Interface, Image Scaler, MCT Generator, Candidate Detector, Confidence Comparator, Position Resizer, Data Grouper, and Detected Result Display, and verification Result of Hardware Implementation with using Virtex5 LX330 FPGA of Xilinx. Verification result with using the images from a camera showed that maximum 32 faces per one frame can be detected at the speed of maximum 149 frame per second.

• Journal of Korean Neurosurgical Society
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• v.53 no.5
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• pp.312-315
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• 2013

Aspergillosis in the central nervous system (CNS) is a very rare disease in immune-competent patients. There was a case of a healthy man without a history of immune-compromised disease who had invasive aspergillosis with unusual radiologic findings. A 48-year-old healthy man with diabetes mellitus, presented with complaints of blurred vision that persisted for one month. Brain magnetic resonance imaging (MRI) showed multiple nodular enhancing lesions on the right cerebral hemisphere. The diffusion image appeared in a high-signal intensity in these areas. Cerebrospinal fluid examination did not show any infection signs. An open biopsy was done and intraoperative findings showed grayish inflammatory and necrotic tissue without a definitive mass lesion. The pathologic result was a brain abscess caused by fungal infection, morphologically aspergillus. Antifungal agents (Amphotericin B, Ambisome and Voriconazole) were used for treatment for 3 months. The visual symptoms improved. There was no recurrence or abscess pocket, but the remaining focal enhanced lesions were visible in the right temporal and occipital area at a one year follow-up MRI. This immune-competent patient showed multiple enhancing CNS aspergillosis in the cerebral hemisphere, which had a good outcome with antifungal agents.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.684-690
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• 2010

Digitalized Image Information is variously used like to substitute or help human's visual ability. Unmanned observation Camera is useful for the preventing disaster, risk factor and object observation but it is mostly to depend on awareness for human's vision. The purpose of this paper is to show that Unmanned Aerial Camera carries out object recognition and autonomous position tracking. when the informations about a specific object are given. For this purpose, we have to solve complicated problems like change according to object movement and variation of color and brightness information with refraction, interference and scattering of light and noise from environmental factors like weather. But, as the first step we limit the scope of this study with simplified environment in this paper. Our goal is the study and experience about object recognition and tracking via simplified environment with unmanned aerial camera. We obtained successful results of this study and experiment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.227-232
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• 2003

Non-intrusive methods based on active remote IR illumination for eye tracking is important for many applications of vision-based man-machine interaction. One problem that has plagued those methods is their sensitivity to lighting condition change. This tends to significantly limit their scope of application. In this paper, we present a new real-time eye detection and tracking methodology that works under variable and realistic lighting conditions. eased on combining the bright-pupil effect resulted from IR light and the conventional appearance-based object recognition technique, our method can robustly track eyes when the pupils are not very bright due to significant external illumination interferences. The appearance model is incorporated in both eyes detection and tracking via the use of support vector machine and the mean shift tracking. Additional improvement is achieved from modifying the image acquisition apparatus including the illuminator and the camera.

• Journal of Internet of Things and Convergence
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• v.5 no.1
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• pp.1-6
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• 2019

This study was intended to verify the impact on the quality of service for employees of youth training facilities. The purpose of this study is to provide basic data for improving service quality by analyzing the factors influencing service quality of youth training facility workers. Data were collected from 110 youth training facilities in Busan. The results showed that social support, emotional labor and self-efficacy had a static effect on the quality of service. Based on the results of this study, the following suggestions were made. First, in order to enhance social support, it is necessary to strengthen regular networking with other agency workers, interview with middle managers, and counseling. Second, to raise emotional labor, it is necessary to imprint a sense of mission as a youth leader. Psychological and emotional programs should also be developed and implemented. Third, in order to increase the self-efficacy, it is necessary to strengthen the administrative super vision and strengthen related education such as image making.

• Journal of KIISE
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• v.45 no.1
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• pp.30-35
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• 2018

GuessWhat?! is a game in which two machine players, composed of questioner and answerer, ask and answer yes-no-N/A questions about the object hidden for the answerer in the image, and the questioner chooses the correct object. GuessWhat?! has received much attention in the field of deep learning and artificial intelligence as a testbed for cutting-edge research on the interplay of computer vision and dialogue systems. In this study, we discuss the objective function and characteristics of the GuessWhat?! game. In addition, we propose a simple solver for GuessWhat?! using a simple rule-based algorithm. Although a human needs four or five questions on average to solve this problem, the proposed method outperforms state-of-the-art deep learning methods using only two questions, and exceeds human performance using five questions.