• Journal of Korean Neurosurgical Society
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• v.61 no.1
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• pp.60-65
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• 2018

Objective : Choroidal metastases (CMs) are the most common intraocular tumor. Management is mainly radiation therapy with goals of pain control and visual improvement. However, many radiation-related complications are reported. Since gamma knife radiosurgery (GKS) for CM was first reported in 1995, few cases have been reported. We report 7 cases of CMs treated with GKS. Methods : From April 2011 to November 2014, 7 patients with CM underwent GKS. Their median age at treatment was 64 years (range, 51-71 years). Four males and three females were treated. Lung cancer was the most common primary pathology, followed by renal cell carcinoma and stomach cancer. Four patients had multiple cerebral lesions and were treated simultaneously for choroidal lesions. The median marginal dose of 20 Gy (range, 15-25 Gy) was administered at the 50% isodose line. Results : Median follow-up period after GKS was 8 months (range, 2-38.3 months). Four patients expired due to underlying malignancy progression. Except for two patients who were not followed with magnetic resonance image after GKS, all patients showed size reduction in the treated lesions, but a new choroidal lesion appeared in one patient and one recurred. Six of seven patients reported subjectively improved visual symptoms. Visual acuity improved in 2 patients, and 2 were stable upon objective examination. One patient showed no improvement in visual acuity, but ocular pain was relieved; another patient showed improved vision and tumor remission, but visual deterioration recurred. Conclusion : GKS was shown to be safe and effective and should be considered for CM treatment.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.137-145
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• 2004

In this paper, a new algorithm for the segmentation of the multi moving objects at the 3 dimension space and the method of measuring the distance from the camera to the moving object by using stereo video monitoring system is proposed. It get the input image of left and right from the stereo video monitoring system, and the area of the multi moving objects segmented by using adaptive threshold and PRA(pixel recursive algorithm). Each of the object segmented by window mask, then each coordinate value and stereo disparity of the multi moving objects obtained from the window masks. The distance of the multi moving objects can be calculated by this disparity, the feature of the stereo vision system and the trigonometric function. From the experimental results, the error rate of a distance measurement be existed within 7.28％, therefore, in case of implementation the proposed algorithm, the stereo security system, the automatic moving robot system and the stereo remote control system will be applied practical application.

• Journal of Navigation and Port Research
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• v.32 no.5
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• pp.355-361
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• 2008

Stereo matching is one of the most active research areas in computer vision. In this paper, we propose a stereo matching scheme using genetic algorithm for object depth recognition. The proposed approach considers the matching environment as an optimization problem and finds the optimal solution by using an evolutionary strategy. Accordingly, genetic operators are adapted for the circumstances of stereo matching. An individual is a disparity set. Horizontal pixel line of image is considered as a chromosome. A cost function is composed of certain constraints which are commonly used in stereo matching. Since the cost function consists of intensity, similarity and disparity smoothness, the matching process is considered at the same time in each generation. The LoG(Laplacian of Gaussian) edge is extracted and used in the determination of the chromosome. We validate our approach with experimental results on stereo images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.142-152
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• 2016

GPS is not able to be used for indoor positioning and currently most of techniques emerging to overcome the limit of GPS utilize private wireless networks. However, these methods require high costs for installation and maintenance, and they are inappropriate to be used in the place where precise positioning is needed as in indoor parking lots. This paper proposes a vehicular indoor positioning method based on QR-code recognition. The method gets an absolute coordinate through QR-code scanning, and obtain the location (an relative coordinate) of a black-box camera using the tilt and roll angle correction through affine transformation, scale transformation, and trigonometric function. Using these information of an absolute coordinate and an relative one, the precise position of a car is estimated. As a result, average error of 13.79cm is achieved and it corresponds to just 27.6% error rate in contrast to 50cm error of the recent technique based on wireless networks.

• The KIPS Transactions:PartA
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• v.14A no.5
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• pp.301-308
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• 2007

This paper proposes high performance coprocessor architecture for real time dense disparity computation based on a phase-based binocular stereo matching technique called local weighted phase-correlation(LWPC). The algorithm combines the robustness of wavelet based phase difference methods and the basic control strategy of phase correlation methods, which consists of 4 stages. For parallel and efficient hardware implementation, the proposed architecture employs SIMD(Single Instruction Multiple Data Stream) architecture for each functional stage and all stages work on pipelined mode. Such that the newly devised pipelined linear array processor is optimized for the case of row-column image processing eliminating the need for transposed memory while preserving generality and high throughput. The proposed architecture is implemented with Xilinx HDL tool and the required hardware resources are calculated in terms of look up tables, flip flops, slices, and the amount of memory. The result shows the possibility that the proposed architecture can be integrated into one chip while maintaining the processing speed at video rate.

• The Journal of the Korea Contents Association
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• v.11 no.6
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• pp.98-105
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• 2011

Recent advances in computer technologies support real-time image processing and special effects on personal computers. This paper presents and analyzes a real-time interactive video system. The motivation of this work is to realize an artistic concept that aims at transforming the timeline visual variations in a video of sea water waves into sound in order to provide an audience with an experience of overlapping themselves onto the nature. In practice, the video of sea water waves taken on a beach is processed using an optical flow algorithm in order to extract the information of visual variations between the video frames. This is then masked by the silhouette of an audience and the result is projected on a gallery space. The intensity information is extracted from the resulting video and translated into piano sounds accordingly. This work generates an interactive space realizing the intended concept.

• Journal of Broadcast Engineering
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• v.21 no.6
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• pp.913-919
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• 2016

In this paper, we propose the visual tracking algorithm that takes advantage of multiple random walkers. We first show the tracking method based on support vector machine as [1] and suggest a method that suppresses feature vectors extracted from backgrounds while preserve features vectors from foregrounds. We also show how to discriminate between foregrounds and backgrounds. Learned by reducing influences of backgrounds, support vector machine can clearly distinguish foregrounds and backgrounds from the image whose target objects are similar to backgrounds and occluded by another object. Thus, the algorithm can track target objects well. Furthermore, we introduce a simple method improving tracking speed. Finally, experiments validate that proposed algorithm yield better performance than the state-of-the-art trackers on the widely-used benchmark dataset with high speed.

• Journal of Broadcast Engineering
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• v.23 no.5
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• pp.636-641
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• 2018

Recently, the digital signages display not only the rectangular shapes but also the various shapes and sizes. The high-resolution large-screen display monitors have evolved to multi-vision modes in which several screens are connected to one another. In this paper, we present the structure of an atypically shaped signage system in which the ROI changes with the rotation of the multiple displays. The inclination angle of the monitor is calculated by taking the output value of the gyro sensor inter-locked with the Arduino, and an image in which the position of the four corners is varied according to the rotation angle by using the polar coordinate system. In order to display images in the multi-screen environment, multiple displays with a gyro sensor were controlled using serial communication. As the result, we have obtained the flexibly moving monitor systems with associated images fitting in them.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.4
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• pp.249-256
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• 2015

Shadow is a common physical phenomenon in natural images and may cause problems in computer vision tasks. Therefore, shadow removal is an essential preprocessing process for effective moving object tracking in video image. In this paper, we proposed the method of shadow removal algorithm using chromaticity, brightness distortion and direction of shadow candidate. The proposed method consists of two steps. First, removal process of primary shadow candidate region by using chromaticity, brightness and distortion. The second stage applies the final shadow candidate region to obtain a direction feature of shadow which is estimated by the thinning algorithm after calculating the lowest pixel position of the moving object. To verify the proposed approach, some experiments are conducted to draw a compare between conventional method and that of proposed. Experimental results showed that proposed methodology is simple, but robust and well adaptive to be need to remove a shadow removal operation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.9
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• pp.5446-5451
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• 2014

Because there are some mistakes by hand in processing electronic maps using a navigation terminal, this paper proposes an automatic offline recognition for traffic signs, which are considered ingredient navigation information. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), which have been used widely in the field of 2D face recognition as computer vision and pattern recognition applications, was used to recognize traffic signs. First, using PCA, a high-dimensional 2D image data was projected to a low-dimensional feature vector. The LDA maximized the between scatter matrix and minimized the within scatter matrix using the low-dimensional feature vector obtained from PCA. The extracted traffic signs under a real-world road environment were recognized successfully with a 92.3% recognition rate using the 40 feature vectors created by the proposed algorithm.