• Journal of Fashion Business
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• v.23 no.1
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• pp.103-115
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• 2019

In this study, we provided examples of light emitting diodes (LEDS) in everyday sportswear and confirmed their usefulness to provide functionality, aesthetics, and entertainment. One type of sports jacket and one set of sportswear were designed and manufactured using LEDs and made available to the general public for use in daily life to provide functionality, aesthetics, and entertainment. To generate digital images, a textural design of a circuit image was developed and applied, and the LEDs were placed on the developed textile in an attempt to merge the LEDs with the design. The product was equipped with a tilt sensor and produced a randomly lighted jacket with LEDs that adjusted according to movement. The LEDs turned on in the desired location by lifting the arm during night sports activities. The tricolor of NEO PIXEL LEDs lit randomly and its rhythmical design could be maximized when moving or exercising outdoors, and also for entertainment. The role of creating interest for lively and unexpected pleasures and the aesthetic beauty of LED lights were also obtained. There was no inconvenience or restriction of movement by LEDs or internal structures using the hot-melting technique, and the removable attachment of the device made it easier to wash.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.145-148
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• 2016

In this paper, we propose a design of Intra Prediction angular mode decision for high-performance HEVC encoder. Intra Prediction works by performing all 35 modes for efficient encoding. However, in order to process all of the 35 modes, the computational complexity and operational time required are high. Therefore, this paper proposes comparing the difference in the value of the original image pixel, using an algorithm that determines Angular mode efficiently. This new algorithm reduces the Hardware size. The hardware which is proposed was designed using Verilog HDL and was implemented in 65nm technology. Its gate count is 14.9k and operating speed is 2GHz.

• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.60-66
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• 2019

In this paper, we propose a new free-view three-dimensional (3D) computational reconstruction of integral imaging to improve the visual quality of reconstructed 3D images when low-resolution elemental images are used. In a conventional free-view reconstruction, the visual quality of the reconstructed 3D images is insufficient to provide 3D information to applications because of the shift and sum process. In addition, its processing speed is slow. To solve these problems, our proposed method uses a pixel rearrangement technique (PERT) with locally selective elemental images. In general, PERT can reconstruct 3D images with a high visual quality at a fast processing speed. However, PERT cannot provide a free-view reconstruction. Therefore, using our proposed method, free-view reconstructed 3D images with high visual qualities can be generated when low-resolution elemental images are used. To show the feasibility of our proposed method, we applied it to optical experiments.

• Nuclear Engineering and Technology
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• v.51 no.2
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• pp.439-443
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• 2019

To improve the noise characteristics, software-based noise reduction algorithms are widely used in cadmium zinc telluride (CZT) pixelated semiconductor gamma camera system. The purpose of this study was to develop an improved median filtering algorithm using a thresholding method for noise reduction in a CZT pixelated semiconductor gamma camera system. The gamma camera system simulated is a CZT pixelated semiconductor detector with a pixel-matched parallel-hole collimator and the spatial resolution phatnom was designed with the Geant4 Application for Tomography Emission (GATE). In addition, a noise reduction algorithm with a median filter using an improved thresholding method is developed and we applied our proposed algorithm to an acquired spatial resolution phantom image. According to the results, the proposed median filter improved the noise characteristics compared to a conventional median filter. In particular, the average for normalized noise power spectrum, contrast to noise ratio, and coefficient of variation results using the proposed median filter were 10, 1.11, and 1.19 times better than results using conventional median filter, respectively. In conclusion, our results show that the proposed median filter using improved the thresholding method results in high imaging performance when applied in a CZT semiconductor gamma camera system.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.753-762
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• 2021

Google provides mapping services using satellite imagery, this is widely used for the study. Since about 20 years ago, research and business using drones have been expanding. Pix4D is widely used to create 3D information models using drones. This study compared the distance error by comparing the result of the road construction site with the DSM data of Google Earth and Pix4 D. Through this, we tried to understand the reliability of the result of distance measurement in Google Earth. A DTM result of 3.08 cm/pixel was obtained as a result of matching with 49666 key points for each image. The length and altitude of Pix4D and Google Earth were measured and compared using the obtained PCD. As a result, the average error of the distance based on the data of Pix4D was measured to be 0.68 m, confirming that the error was relatively small. As a result of measuring the altitude of Google Earth and Pix4D and comparing them, it was confirmed that the maximum error was 83.214m, which was measured using satellite images, but the error was quite large and there was inaccuracy. Through this, it was confirmed that there are difficulties in analyzing and acquiring data at road construction sites using Google Earth, and the result was obtained that point cloud data using drones is necessary.

• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.601-607
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• 2022

In recent years, monitoring of spent nuclear fuel inside dry cask storage has become an important area of national security. Muon tomography is a useful method for monitoring spent nuclear fuel because it uses high energy muons that penetrate deep into the target material and provides a 3-D structure of the inner materials. We designed a muon tomography system consisting of four 2-D position sensitive detector and characterized and optimized the system parameters. Each detector, measuring 200 × 200 cm², consists of a plastic scintillator, wavelength shifting (WLS) fibers and, SiPMs. The reconstructed image is obtained by extracting the intersection of the incoming and outgoing muon tracks using a Point-of-Closest-Approach (PoCA) algorithm. The Geant4 simulation was used to evaluate the performance of the muon tomography system and to optimize the design parameters including the pixel size of the muon detector, the field of view (FOV), and the distance between detectors. Based on the optimized design parameters, the spent fuel assemblies were modeled and the line profile was analyzed to conduct a feasibility study. Line profile analysis confirmed that muon tomography system can monitor nuclear spent fuel in dry storage container.

• Journal of IKEEE
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• v.26 no.2
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• pp.240-248
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• 2022

Floating-point images that express pixel information as real numbers are used in HDR images. There have been various researches on efficient median filter algorithms, but most of them are applicable to 8-bit depth images and there are only a few number of algorithms applicable to floating-point images, including Gil and Werman's algorithm. In this paper, we propose a median filter algorithm that works efficiently on floating-point images by improving Kim's algorithm, which improved Gil and Werman's algorithm. Experimental results show that the execution time is improved by about 10% compared to the Kim's algorithm by reducing the redundant work for the repetitively used binary search tree and applying the inverted index.

• Journal of Korea Multimedia Society
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• v.25 no.7
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• pp.895-902
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• 2022

Building segmentation using satellite imagery such as EO (Electro-Optical) and SAR (Synthetic-Aperture Radar) images are widely used due to their various uses. EO images have the advantage of having color information, and they are noise-free. In contrast, SAR images can identify the physical characteristics and geometrical information that the EO image cannot capture. This paper proposes a learning framework for efficient building segmentation that consists of a teacher-student-based privileged knowledge distillation and deformable convolution block. The teacher network utilizes EO and SAR images simultaneously to produce richer features and provide them to the student network, while the student network only uses EO images. To do this, we present objective functions that consist of Kullback-Leibler divergence loss and knowledge distillation loss. Furthermore, we introduce deformable convolution to avoid pixel-level noise and efficiently capture hard samples such as small and thin buildings at the global level. Experimental result shows that our method outperforms other methods and efficiently captures complex samples such as a small or narrow building. Moreover, Since our method can be applied to various methods.

• Tribology and Lubricants
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• v.38 no.4
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• pp.128-135
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• 2022

In the product development process, the reliability of the product can be secured through durability tests. However, since the durability test method is expensive and time consuming, a method to save time and money by utilizing virtual product development (VPD) is required. However, research on the accuracy of the results of virtual product development is required. In this paper, an accelerated durability test was designed and conducted using a planetary gear decelerator. And an analysis model under the same conditions was created and simulated. To correlate the results of the experiment with the results of the analytical model, created a model that can discriminate the wear region using one of the data mining methods, the k-means algorithm method and HSV (Hue, Saturation, Value). The wear area is compared by counting the number of pixels defined as wear through a discrimination model. A similar ratio was calculated by comparing the pixel ratio of the area determined as wear in the entire area. It showed a similar ratio of about 70%, and it is necessary to improve the discrimination method.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.7-13
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• 2021

This paper presents an vulnerable road user (VRU) classification and tracking algorithm using vision and LiDAR sensor fusion method for urban autonomous driving. The classification and tracking for vulnerable road users such as pedestrian, bicycle, and motorcycle are essential for autonomous driving in complex urban environments. In this paper, a real-time object image detection algorithm called Yolo and object tracking algorithm from LiDAR point cloud are fused in the high level. The proposed algorithm consists of four parts. First, the object bounding boxes on the pixel coordinate, which is obtained from YOLO, are transformed into the local coordinate of subject vehicle using the homography matrix. Second, a LiDAR point cloud is clustered based on Euclidean distance and the clusters are associated using GNN. In addition, the states of clusters including position, heading angle, velocity and acceleration information are estimated using geometric model free approach (GMFA) in real-time. Finally, the each LiDAR track is matched with a vision track using angle information of transformed vision track and assigned a classification id. The proposed fusion algorithm is evaluated via real vehicle test in the urban environment.