• Proceedings of the Korean Fiber Society Conference
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• 2007.11a
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• pp.499-500
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• 2007

• 한국생물공학회:학술대회논문집
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• 2005.10a
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• pp.421-421
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• 2005

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2010.04a
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• pp.149-150
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• 2010

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4968-4986
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• 2017

In this paper, we primarily address the difficulty of automatic generation of a plausible depth map from a single image in an unstructured environment. The aim is to extrapolate a depth map with a more correct, rich, and distinct depth order, which is both quantitatively accurate as well as visually pleasing. Our technique, which is fundamentally based on a preexisting DepthTransfer algorithm, transfers depth information at the level of superpixels. This occurs within a framework that replaces a pixel basis with one of instance-based learning. A vital superpixels feature enhancing matching precision is posterior incorporation of predictive semantic labels into the depth extraction procedure. Finally, a modified Cross Bilateral Filter is leveraged to augment the final depth field. For training and evaluation, experiments were conducted using the Make3D Range Image Dataset and vividly demonstrate that this depth estimation method outperforms state-of-the-art methods for the correlation coefficient metric, mean log10 error and root mean squared error, and achieves comparable performance for the average relative error metric in both efficacy and computational efficiency. This approach can be utilized to automatically convert 2D images into stereo for 3D visualization, producing anaglyph images that are visually superior in realism and simultaneously more immersive.

• Journal of Korea Multimedia Society
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• v.20 no.9
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• pp.1491-1501
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• 2017

In this paper, we propose a method to measure respiration rate by dividing the respiration related region in depth image using level set method. In the conventional method, the respiration related region was separated using the pre-defined region designated by the user. We separate the respiration related region using level set method combining shape prior knowledge. Median filter and clipping are performed as a preprocessing method for noise reduction in the depth image. As a feasibility test, respiration activity was recorded using depth camera in various environments with arm movements or body movements during breathing. Respiration activity was also measured simultaneously using a chest belt to verify the accuracy of calculated respiration rate. Experimental results show that our proposed method shows good performance for respiration rate estimation in various situation compared with the conventional method.

• Journal of Environmental Science International
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• v.13 no.9
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• pp.799-806
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• 2004

The filtration tests were made in cell with a low concentrated suspension. The suspension with a concentration of $C_{M}$=1.14～2.67$\cdot$$10^{-3}$ g/g consists of paper paint and water. The particles in the suspension have a particle size x<1${\mu}m$. The used depth filters consists of glass fibres, which are coated by polymer. The filtration in depth filters accorded in different mechanism, which were explained by physical models. The model which would be allows to make a promise of the filtration reaction. This filter media allows to get a high filtration time and a good separation rate. The Particle distribution is measured by a photon correlation spectroscopy(PCS). PCS measures particle sizes 0.03 ${\mu}m$${\mu}m$ in the suspension. The filtered suspension has a very low concentration Co{\le}5{\times}10_{-4}$ g/g of solid in sample. The PCS also informs us about the number of the particles in the suspension. The makes it possible to calculate the concentration of the in sample.

• Journal of Broadcast Engineering
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• v.16 no.5
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• pp.883-893
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• 2011

In this paper, we propose a novel focus measure that determines in-focus and out-of-focus region in an image. In addition, we achieved extended depth of field by blending the acquired image and Wiener filtered image using a decision map based on the designed focus measure. Since conventional focus measures are based on the amount of high frequency components in an acquired image, the measures may not be accurate if there exist high frequency components in out-of-focused region. To overcome the problem, we designed the novel focus measure based on effective band pass filtering. In simulations and experiments, the proposed method showed better performance than existing methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.200-202
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• 2014

본 논문은 High bit-depth 를 위한 SIMD (Single Instruction, Multiple Data) 명령어 기반 보간 필터 고속화 방법을 제안한다. 픽셀 연산을 기반으로 하는 보간 필터링은 HEVC 복호화기에서 높은 복잡도를 차지하고 있지만 반복적인 산술연산을 수행하기 때문에 SIMD 를 이용한 고속화에 적합한 구조를 가지고 있다. 이러한 이유로 본 논문에서는 보간 필터 연산에 대하여 SIMD 명령어를 이용하여 메모리를 효율적으로 사용하여 고속화하는 방법을 제안한다. 제안하는 기술은 HEVC 참조 소프트웨어 HM 12.0-RExt 4.1 에 기반을 둔 ANSI C 기반 자체 개발 HEVC RExt 복호화기 소프트웨어에서 평균 8.5%의 복호화 속도향상을 보였으며, 보간 필터의 수행 시간을 평균 24.8% 향상시켰다.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.3 no.3
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• pp.1-7
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• 1983

In spite of extensive knowledge of the surface chemistry and the transport mechanism in filtration systems, there is still insufficient understanding of the physical characteristics of suspensions and the system components. Because of this, no filtration mechanisms are mathematically generalized to the full extent. The purpose of this paper is to propose experimental equations for the filtration process. using the tracer study in filter layer. Some of results are as follows. (1) The Volume of the specific deposit (${\sigma}$) in filtration was directly measurable using the tracer study without interrupting the filtration. (2) It was also confirmed that the head loss in filtration was greatly in fluenced by the micro-air babbles. (3) The correction coefficient(f) was introduced into the Kozeny-Carman equation in order to apply it for the clogging filter media. The coefficient(f) was experimentally obtained. The total head loss of the filter media is given by next equation. $${\frac{h}{h_0}}={\frac{1}{L}}{\int}^{z=L}_{z=0}f({\sigma})g({\varepsilon}_0,{\sigma})dz$$ $$f=aexp(-b{\sigma})$$ The above equation was applicable without regard to the variation of the suspension concentration, the filter medium diameter, the filter depth, the filtration velocity, and the amount of aluminum in all continuous filtration experiments. (4) The total head loss was graphically generalized assuming mathematical filtration models I II (see fig. 7,8) (5) The total head loss was obtained from the filtration model in the field filtration conditions. (see fig. 9,10)