• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1320-1326
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• 2018

Digital video equipment is important in the 4th industrial revolution and is widely used in different fields for various purpose. Data of digital video equipment is exposed to noise due to different reasons including user environment and processing and such noise affect output and processing method. This can even cause error, resulting in decreased reliability of the equipment. In this research, it offers algorithm to effectively recover video by removing noise and impulse noise occurring during the process of channel delivery. This proposed algorithm recovers video by exploring valid pixel using directional local mask and noise determination. Then, valid pixel calculated goes through the final output calculation through comparative analysis on estimation. For comparing suggested method and algorithm, simulation is carried out. For checking the function of it, PSNR and profile are analyzed.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.28 no.3
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• pp.273-282
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• 2018

Objectives: Dustiness of nanomaterials is considered as exposure index of essential material. Research on dustiness of nanomaterial is needed to control exposure in workplaces. Method: Dustiness measurement using vortex shaker were installed in the laboratory. Nanomaterials, 1 g, was put in the glass test tube and shaked using vortex shaker. Aerosol dispersed was measured using scanning mobility particle sizer(SMPS) and optical particle counter(OPC). Mass concentration using PVC filter and cassette was measured and TEM grid sampling was conducted. Total particle concentration and size distribution were calculated. Image and chemical composition of particles in the air were observed using transmission electron microscopy and energy dispersive X-ray spectrometer. Eleven different test nanomaterials were used in the study. Results: Rank of mass concentration and particle number concentration were coincided in most cases. Rank of nanomateirals with low concentration were not coincided. Two types of fumed silica had the highest mass concentration and particle number concentration. Indium tin oxide, a mixture of indium oxide and tin oxide, had high mass concentration and particle number concentration. Indium oxide had very low mass concentration and particle number concentration. Agglomeration of nanoparticles in the air were observed in TEM analysis and size distribution. In this study, mass concentration and particle number concentration were coincided and two index can be used together. The range of dustiness in particle number concentration were too wide to measure in one method. Conclusion: Particle number concentration ranged from low concentration to high concentration depend on type of nanomaterial, and varied by preparation and amount of nanomaterial used. Further study is needed to measure dustiness of all nanomaterial as one reference method.

• Korean Journal of Remote Sensing
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• v.22 no.1
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• pp.49-61
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• 2006

The lifting scheme has been found to be a flexible method for constructing scalar wavelets with desirable properties. In this paper, it is extended to the UDAR data compression. A newly developed data compression approach to approximate the UDAR surface with a series of non-overlapping triangles has been presented. Generally a Triangulated Irregular Networks (TIN) are the most common form of digital surface model that consists of elevation values with x, y coordinates that make up triangles. But over the years the TIN data representation has become an important research topic for many researchers due its large data size. Compression of TIN is needed for efficient management of large data and good surface visualization. This approach covers following steps: First, by using a Delaunay triangulation, an efficient algorithm is developed to generate TIN, which forms the terrain from an arbitrary set of data. A new interpolation wavelet filter for TIN has been applied in two steps, namely splitting and elevation. In the splitting step, a triangle has been divided into several sub-triangles and the elevation step has been used to 'modify' the point values (point coordinates for geometry) after the splitting. Then, this data set is compressed at the desired locations by using second generation wavelets. The quality of geographical surface representation after using proposed technique is compared with the original UDAR data. The results show that this method can be used for significant reduction of data set.

• Journal of IKEEE
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• v.25 no.3
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• pp.430-436
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• 2021

The non-contact body temperature measurement system is one of the key factors, which is manage febrile diseases in mass facilities using optical and thermal imaging cameras. Conventional systems can only be used for simple body temperature measurement in the face area, because it is used only a deep learning-based face detection algorithm. So, there is a limit to detecting abnormal symptoms of the infants and young children, who have difficulty expressing their opinions. This paper proposes an improved facial expression recognition algorithm for detecting abnormal symptoms in infants and young children. The proposed method uses an object detection model to detect infants and young children in an image, then It acquires the coordinates of the eyes, nose, and mouth, which are key elements of facial expression recognition. Finally, facial expression recognition is performed by applying a selective sharpening filter based on the obtained coordinates. According to the experimental results, the proposed algorithm improved by 2.52%, 1.12%, and 2.29%, respectively, for the three expressions of neutral, happy, and sad in the UTK dataset.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.101-108
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• 2019

Due to recent improvements in computer processing speed and image processing technology, researches are being actively carried out to combine information from camera with existing GNSS (Global Navigation Satellite System) and dead reckoning. In this study, developed a vision-based positioning assistant algorithm to estimate the distance to the object from stereo images. In addition, GNSS/on-board vehicle sensor/vision based positioning algorithm is developed by combining vision based positioning algorithm with existing positioning algorithm. For the performance analysis, the velocity calculated from the actual driving test was used for the navigation solution correction, simulation tests were performed to analyse the effects of velocity precision. As a result of analysis, it is confirmed that about 4% of position accuracy is improved when vision information is added compared to existing GNSS/on-board based positioning algorithm.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.19-26
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• 2019

In this paper, the classification performance of learning algorithms is compared for TAB digit recognition. The TAB digits that are segmented from TAB musical notes contain TAB lines and musical symbols. The labeling method and non-linear filter are designed and applied to extract fret digits only. The shift operation of the 4 directions is applied to generate more data. The selected models are Bayesian classifier, support vector machine, prototype based learning, multi-layer perceptron, and convolutional neural network. The result shows that the mean accuracy of the Bayesian classifier is about 85.0% while that of the others reaches more than 99.0%. In addition, the convolutional neural network outperforms the others in terms of generalization and the step of the data preprocessing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1468-1473
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• 2018

The importance of communication and data processing is increasing with the advance of the Fourth Industrial Revolution. Hence, the importance of video and data processing technologies, which directly influence the accuracy and reliability of equipment, is also increasing. In this research report we propose an algorithm for calculating the final output by estimating the standard deviation and estimate required for removing AWGN while adapting to changes in the frequency factors of video. This algorithm calculates the final output by checking an estimated value against the effective pixel range, which is obtained from the standard deviation of mask factors. Subsequently, the weighted value is computed, taking into account the filter output. To evaluate the functionality of this algorithm, it is compared with the most-commonly used present method through simulation. The simulation results show that the important features of the image are preserved and efficient noise cancellation performance is demonstrated.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.66-69
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• 2016

In this paper, we suggests a Ka-band LNB considering next-generation UHD satellite TVRO. Since Ka-band has grater attenuation than Ku-band in atmosphere, we designed the low-noise down-converter to improve receiving sensitivity and to extend a dynamic range of receiver. It aims to compensate a quality of ultra high definition transmission signal for rainfall. The low-noise block diagram consists of a three-staged amplifier (LNA), band-pass filter for deleting image (BPF), mixer and IF when considering nonlinear characteristics in the receiver RF front end module. Also, we showed a LNB through optimization processes affecting dynamic range directly in receiver FEM. Asa resuly of experiment, the gain of low-noise down-converter show between 58.5dB and 60.7dB, the noise figure has a high characteristic as 1.38dB. Finally, the phase noise of local oscillator is -63.10dBc at 100MHz offset frequency.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.394-400
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• 2019

Noise removal is one of the required step in processing digital video and there are many researches to develop algorithm that fits with its purpose and environment. However, present impulse noise removal methods are lacking in its function in terms of removing noise in edge and high frequency factors. Therefore, this research has Extended range of masks depending on density to determine noise so that high frequency factors can be preserved. The range of resolution is set based on median and standard deviation of inside resolution after removing impulse noise. afterwards, those resolution within the range are calculated by adding weight to have the final output value. The suggested algorithm has an enhanced function in removing noise in various areas with many edge and high frequency factors than present methods and their functions are compared through simulation.

• Journal of IKEEE
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• v.26 no.3
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• pp.416-421
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• 2022

In this study, we present a fully automated system that combines camera technology with liquid crystal technology to create a polarization camera capable of detecting the partial linear polarization of light reflected from an object. The use of twisted nematic (TN) liquid crystals that electro-optically modulate the polarization plane of light eliminates the need to mechanically rotate the polarizing filter in front of the camera lens. Images obtained using these techniques are imaged by computer software. In addition, liquid crystal panels have been produced in a square shape, but many camera lenses are usually round, and lighting or other driving units are installed around the lens, so space is optimized through the application of a circular liquid crystal display. Through the development of this technology, an electrically switchable and space-optimized liquid crystal polarizer is developed.