• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.403-408
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• 2003

A general meaning of caricaturing is that a representation, especially pictorial or literary, in which the subject's distinctive features or peculiarities are deliberately exaggerated to produce a comic or grotesque effect. In other words, a caricature is defined as a rough sketch(dessin) which is made by detecting features from human face and exaggerating or warping those. There have been developed many methods which can make a caricature image from human face using computer. In this paper, we propose a new caricaturing system. The system uses a real-time image or supplied image as an input image and deals with it on four processing steps and then creates a caricatured image finally. The four Processing steps are like that. The first step is detecting a face from input image. The second step is extracting special coordinate values as facial geometric information. The third step is deforming the face image using local warping method and the coordinate values acquired in the second step. In fourth step, the system transforms the deformed image into the better improved edge image using a fuzzy Sobel method and then creates a caricatured image finally. In this paper , we can realize a caricaturing system which is simpler than any other exiting systems in ways that create a caricatured image and does not need complex algorithms using many image processing methods like image recognition, transformation and edge detection.

• Journal of Broadcast Engineering
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• v.17 no.5
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• pp.838-850
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• 2012

In this paper, we propose a novel algorithm that generates multi-view images by using various image features obtained from the given stereoscopic images. In the proposed algorithm, we first create an intensity gradient saliency map from the given stereo images. And then we calculate a block-based optical flow that represents the relative movement(disparity) of each block with certain size between left and right images. And we also obtain the disparities of feature points that are extracted by SIFT(scale-invariant We then create a disparity saliency map by combining these extracted disparity features. Disparity saliency map is refined through the occlusion detection and removal of false disparities. Thirdly, we extract straight line segments in order to minimize the distortion of straight lines during the image warping. Finally, we generate multi-view images by grid mesh-based image warping algorithm. Extracted image features are used as constraints during grid mesh-based image warping. The experimental results show that the proposed algorithm performs better than the conventional DIBR algorithm in terms of visual quality.

• Korean Journal of Environmental Biology
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• v.20 no.4
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• pp.360-365
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• 2002

The variety and density of entomopathogenic nematodes from the polluted soils of heavy metals were examined. In order to investigate the pollution of heavy metals in soil, 300 sites in kyungsangbuk-do were collected from March to October in 2001. We measured the contents of seven heavy metal elements (Cd, Cu, As, Hg, Pb, Cr^{6+}$, CN) and than cheesed soil of 25 sites with high concentration of heavy metals. The seven strains of nematodes were isolated from seven samples by silkworm host (Bombyx mori mori) and white trap. Isolated nematodes are composed of two families, one order. The members of Rhabditida were isolated in the soil with mean Cd content of 0.870 ppm. And they were isolated in the soil samples with As content less than 0.745 ppm. However they were isolated regardless of concentration of Cu and Pb. The members of Cylindrocorpidae were isolated in the soil samples with Cr^{6+}$ content less than 0.05 ppm. Any entomopathogenic nematode was not detected in the CN polluted soil. Isolated nematodes successfully cultured on the silkworm host and were confirmed the pathogenicity, multiplicity, and tolerance against various condition of preservation. Which proved its potential usefulness as biological agent.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.02a
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• pp.361-361
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• 2013

비냉각 적외선 검출소자는 빛이 전혀 없는 환경에서도 사물을 감지하는 열상장비의 핵심소자이다. 마이크로볼로미터 적외선 검출기는 상온에서 동작하며, 온도안정화를 위해 TEC를 장착하여 진공패키지로 조립된다. 패키지는 진공을 유지할 수 있도록 일반적으로 메탈로 제작되며, 단가 감소 및 생산성 증대를 위해 wafer level packaging 방법을 이용한다. 마이크로볼로미터의 특성은 패키지의 진공 변화에 매우 민감하다. 센서의 감도를 증가시키기 위해서는 진공환경을 유지해야 한다. 볼로미터 소자의 특성은 상압에서 열전도는 기판과 멤브레인 사이의 에어갭을 통해 열손실을 야기하므로 센서의 반응도가 현저히 줄어든다. 에어갭이 1 um 정도 되더라도 그 사이에 존재하는 열전도가 가능하므로 진공을 유지하여 열고립 상태를 증대시킬 수 있다. 이에 본 연구에서는 소자의 동작시 압력, 즉 진공도가 볼로미터 소자의 반응도 특성에 미치는 영향을 조사하였다. 마이크로볼로미터 소자는 $2{\times}8$ 어레이 형태로 제작하였으며, metal pad를 각 단위셀에 배치하였으며, 공통전극으로 한 개의 metal pad를 넣어 설계하였다. 흡수체로써 VOx를 사용하였으며, 열 고립구조를 위해 2.5 um 공명 흡수층의 floating 구조로 멤브레인을 형성하였다. 진공패키지는 메탈패키지를 제작하여 볼로미터 칩을 TEC 위에 장착하였으며, 신호의 감지를 위해 가변저항을 매칭시켰다. 반응도는 신호 대 잡음 값을 획득하여 소자에 도달하는 적외선 에너지에 대해 반응하는 값을 계산에 의해 얻어내는 것이다. 픽셀 크기는 $50{\times}50$ um이며, 패키지 조립 공정 후 온도변화에 따른 저항 측정을 통해 TCR 값을 얻었다. 이때 TCR은 약 -2.5%/K으로 나타났다. $2{\times}8$의 4개 단위소자에 대해 측정한 값은 균일하게 TCR 값이 나타났다. 광반응 특성은 볼로미터 단위소자에 대해서 먼저 고진공(5e-6 torr) 하에서 측정하였으며, 반응도는 25,000 V/W의 값을 나타내었고, 탐지도는 약 2e+8 $cmHz_{1/2}$/W로 나타났다. 패키지의 압력 조절을 위해 TMP 및 로터리 펌프를 이용하여 100 torr에서 1e-4 torr의 범위에서 압력조절 밸브를 이용하여 질소가스의 압력으로 진공도를 변화시켰다. 적외선 반응신호는 압력이 증가함에 따라 감소하였으며, 2e-1 torr의 압력에서 신호의 크기가 감소하기 시작하여 5 torr에서 반응도의 1/2 값을 나타냄을 알 수 있었다. 30 torr 이상에서는 신호가 잡음값 과거의 동일하여 신호대 잡음비가 1로 나타남을 알 수 있었다. 또한 진공도 변화에 대해, 흑체온도에 따른 반응도 및 탐지도의 특성을 조사한 결과를 발표한다. 반응도의 증가를 위해 진공도는 진공도는 1e-2 torr 이하의 압력을 유지해야 함을 본 실험을 통해 알 수 있었다.

• Fire Science and Engineering
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• v.34 no.2
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• pp.94-96
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• 2020

In November 2013, a case of sustained combustion of a female body was encountered in a Korean farming village. The body was almost completely incinerated from the neck to the knees, and other parts of the body, such as the head, arms, lower legs, and feet, were slightly damaged. The most likely external ignition source was the flame from a matchstick. The elderly woman was found incinerated on the floor of the living room, while other objects in the house were largely undamaged except for having a brown oily or greasy coating. Flammable substances were not detected from the woman's intact pieces of clothing and socks, and her muscular tissues did not contain toxic chemicals. The concentration of carboxyhemoglobin in her peripheral blood was 11% and that of ethyl alcohol in her aqueous humor was below 0.010%. An autopsy failed to determine the exact cause of death because of excessive charring.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.163-169
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• 2020

Recently, research on automation and unmanned operation of machines in the industrial field has been conducted with the advent of AI, Big data, and the IoT, which are the core technologies of the Fourth Industrial Revolution. The machines for these automation processes are controlled based on the data collected from the sensors attached to them, and further, the processes are managed. Conventionally, the abnormalities of sensors are periodically checked and managed. However, due to various environmental factors and situations in the industrial field, there are cases where the inspection due to the failure is not missed or failures are not detected to prevent damage due to sensor failure. In addition, even if a failure occurs, it is not immediately detected, which worsens the process loss. Therefore, in order to prevent damage caused by such a sudden sensor failure, it is necessary to identify the failure of the sensor in an embedded system in real-time and to diagnose the failure and determine the type for a quick response. In this paper, a deep neural network-based fault diagnosis system is designed and implemented using Raspberry Pi to classify typical sensor fault types such as erratic fault, hard-over fault, spike fault, and stuck fault. In order to diagnose sensor failure, the network is constructed using Google's proposed Inverted residual block structure of MobilieNetV2. The proposed scheme reduces memory usage and improves the performance of the conventional CNN technique to classify sensor faults.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.62-68
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• 2012

Steady-State Visually Evoked Potentials (SSVEP) are natural response signal associated with the visual stimuli with specific frequency. By using SSVEP, occipital lobe region is electrically activated as frequency form equivalent to stimuli frequency with bandwidth from 3.5Hz to 75Hz. In this paper, we propose an experimental paradigm for analyzing EEGs based on the properties of SSVEP. At first, an experiment is performed to extract frequency feature of EEGs that is measured from the image-based visual stimuli associated with specific objective with affordance and object-related affordance is measured by using mirror neuron system based on the frequency feature. And then, linear discriminant analysis (LDA) method is applied to perform the online classification of the objective pattern associated with the EEG-based affordance data. By using the SSVEP measurement experiment, we propose a Brain-Computer Interface (BCI) system for recognizing user's inherent intentions. The existing SSVEP application system, such as speller, is able to classify the EEG pattern based on grid image patterns and their variations. However, our proposed SSVEP-based BCI system performs object pattern classification based on the matters with a variety of shapes in input images and has higher generality than existing system.