• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.11
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• pp.2429-2434
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• 2010

In this paper, we propose a method to extract and analyze palm line with fuzzy method. In order to extract the palm part, we transform the original RGB color space to YCbCr color space and extract sin colors ranging Y:65-255, Cb:25-255, Cr:130-255 and use it as a threshold. Possible noise is removed by 8-directional contour tracking algorithm and morphological characteristic of the palm. Then the edge is extracted from that noise-free image by stretching method and sobel mask Then the fuzzy binarization algorithm is applied to remove any minute noise so that we have only the palm lines and the boundary of the hand. Since the palm line reading is done with major lines, we use the morphological characteristics of the analyzable palm lines and fuzzy inference rules. Experiment verifies that the proposed method is better in visibility and thus more analyzable in palm reading than the old method.

• Journal of Korea Multimedia Society
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• v.6 no.3
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• pp.508-517
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• 2003

This paper presents perceptual model with a stochastic multiresolution characteristic that can be applied with watermark embedding in the biorthogonal wavelet domain. The perceptual model with adaptive watermarking algorithm embeds at the texture and edge region for more strongly embedded watermark by the SSQ. The watermark embedding is based on the computation of a NVF that has local image properties. This method uses non- stationary Gaussian and stationary Generalized Gaussian models because watermark has noise properties. The particularities of embedding in the stationary GG model use shape parameter and variance of each subband regions in multiresolution. To estimate the shape parameter, we use a moment matching method. Non-stationary Gaussian model uses the local mean and variance of each subband. The experiment results of simulation were found to be excellent invisibility and robustness. Experiments of such distortion are executed by Stirmark 3.1 benchmark test.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.4
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• pp.443-452
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• 2008

To deduce 3D linear information which express shapes of buildings out of airphoto by fusion of airphoto and LiDAR data, this research went through 2 process. First, research made LiDAR data into projected data of 2D based on airphoto. For this, the virtual points were added to solve the visual problem of building boundary area which has poor information because the attribute in LiDAR data. Research construct irregular triangular nets from modified LiDAR data and judge visual triangular nets out of image. Through this, research can make reference to information of triangular nets in each image pixel. Second, 3D information was extracted from stereo images segments by combining extracted information of visible region and 2D irregular triangular nets. Matching way based on TIN for segments from stereo images was used. Matching condition based on TIN can improve about 20% of edge matching accuracy compared to existing quadrilateral condition of epipolar geometry.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.180-191
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• 2016

When up-scaling algorithms for visible light images are applied to infrared (IR) images, they rarely work because IR images are usually blurred. In order to solve such a problem, this paper proposes an up-scaling algorithm for IR images. We employ adaptive dynamic range encoding (ADRC) as a simple classifier based on the observation that IR images have weak details. Also, since human visual systems are more sensitive to edges, our algorithm focuses on edges. Then, we add pre-processing in learning phase. As a result, we can improve visibility of IR images without increasing computational cost. Comparing with Anchored neighborhood regression (A+), the proposed algorithm provides better results. In terms of just noticeable blur, the proposed algorithm shows higher values by 0.0201 than the A+, respectively.

• Current Optics and Photonics
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• v.1 no.4
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• pp.351-357
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• 2017

This paper proposes a LED bicycle headlamp with a wide viewing angle to help bicyclists see the front effectively and because of its high visibility to reduce the risks of accidents around intersections or blind spots. The wide viewing angle was determined to be $28^{\circ}$ because it can illuminate a 5 m wide area 10 m away. Therefore, the road conditions of the intersection can be observed with the bicycle handlebar tilted slightly to the left or right. The headlamp has a compact reflector with a width of 30 mm, height of 27 mm, and length of 17 mm. Owing to its size, a change in the position of a light source leads to severe changes in light distribution. Therefore, the tolerance of the source position was analyzed by a simulation. The tolerance was ${\pm}0.5mm$ at the X, Y and Z axes within a less centered aiming range of ${\pm}1^{\circ}$. Finally, the prototype of the bicycle headlamp was made and the light distribution was measured by an automotive headlamp light measurement system. The experimental results indicate that the headlamp illuminates a 5 m wide area with an edge light of 3.2 lx as well as meeting the K-mark regulation.

• The KIPS Transactions:PartD
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• v.13D no.5 s.108
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• pp.691-698
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• 2006

The companies need the enterprise-wide support environment to build the competency to gather VOM(Voice of Market) in the process of preparing and implementing the strategy and to help establishing and managing the business process in order to secure the continuous competitive edge The enterprise-wide support environment to establish, operate, improve and evaluate the business process must be carried out. In this paper we define the method to define process and business rule in order to enable accurate execution of the process. Furthermore, collection and refection of accurate data concerning the competency of individuals, the subjects of the process execution, allows prevention of weakness of the process execution result and is the basis for identifying the areas of improvement. Therefore, high visibility can be attained through the work knowledge and processes presented in rules, and it can help firmly establish the process centered work culture (or system) in the organization by process improvement strictly based on data.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.38 no.1
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• pp.43-57
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• 2002

This paper introduces an analysis method to predicting the flow characteristic of flow field around otter board In order to develope a high performance model. In this experiment, it is used a numerical analysis of flow field through CFD(Computational Fluid Dynamic), PIV method in which quantitative, qualitative evaluation is possible. In this experiment, it is used PIV method with flow filed image around otter board in order to analysis of flow characteristic. The result compared flow pattern with analysis result through CFD and also measurement result of lift and drag force coefficient carried out in CWC(Circulating Water Channel). The numerical analysis result is matched well with experiment result of PIV in the research and it is able to verify In the physical aspect. The result is as follows ; (1) It was carried out visibility experiment using laser light sheet, and picture analysis through PIV method in order to analysis fluid field of otter-board. As a result, the tendency of qualitative fluid movement only through the fluid particle's flow could be known. (2) Since PIV analysis result is quantitative, this can be seen in velocity vector distributions, instantaneous streamline contour, and average vorticity distributions through various post processing method. As a result, the change of flow field could be confirmed. (3) At angle of attack 24$^{\circ}$ where It Is shown maximum spreading force coefficient, the analysis result of CFD and PIV had very similar flow pattern. In both case, at the otter-board post edge a little boundary layer separation was seen, but, generally they had a good flow (4) As the result of post processing with velocity vector distributions, instantaneous streamline contour and average vorticity distributions by PIV, boundary layer separation phenomenon started to happen from angle of attack 24$^{\circ}$, and from over angle of attack 28$^{\circ}$, it happen at leading edge side with the width enlarged.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4717-4737
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• 2017

Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.

• Journal of Internet Computing and Services
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• v.19 no.5
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• pp.43-54
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• 2018

Images taken in haze weather are characteristic of low contrast and poor visibility. The process of reconstructing clear-weather image from a hazy image is called dehazing. The main challenge of image dehazing is to estimate the transmission map or depth map for an input hazy image. In this paper, we propose a single image dehazing method by utilizing the Generative Adversarial Network(GAN) for accurate depth map estimation. The proposed GAN model is trained to learn a nonlinear mapping between the input hazy image and corresponding depth map. With the trained model, first the depth map of the input hazy image is estimated and used to compute the transmission map. Then a guided filter is utilized to preserve the important edge information of the hazy image, thus obtaining a refined transmission map. Finally, the haze-free image is recovered via atmospheric scattering model. Although the proposed GAN model is trained on synthetic indoor images, it can be applied to real hazy images. The experimental results demonstrate that the proposed method achieves superior dehazing results against the state-of-the-art algorithms on both the real hazy images and the synthetic hazy images, in terms of quantitative performance and visual performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6C
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• pp.349-354
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• 2011

Passive millimeter wave imaging has the capability of detecting concealed objects under clothing. Also, passive millimeter imaging can obtain interpretable images under low visibility conditions like rain, fog, smoke, and dust. However, the image quality is often degraded due to low spatial resolution, low signal level, and low temperature resolution. This paper addresses image registration and fusion between passive millimeter images and visual images. The goal of this study is to combine and visualize two different types of information together: human subject's identity and concealed objects. The image registration process is composed of body boundary detection and an affine transform maximizing cross-correlation coefficients of two edge images. The image fusion process comprises three stages: discrete wavelet transform for image decomposition, a fusion rule for merging the coefficients, and the inverse transform for image synthesis. In the experiments, various types of metallic and non-metallic objects such as a knife, gel or liquid type beauty aids and a phone are detected by passive millimeter wave imaging. The registration and fusion process can visualize the meaningful information from two different types of sensors.