• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.12
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• pp.1397-1404
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• 2014

Grab cranes are used for multi-purpose when the sand and soil are deposited into harbor wharf or the undersea construction is performed. Among the components of crane grab, the wire drum and disc brake pad are key expendables and have disadvantages that lot of heat is generated and very expensive when replacing them. In this study, the thermal image analysis for the disc brake, which works with wire drum of the crane is suggested. The suggested system performs the pad thermal diagnosis through the thermal image using the characteristics that the disc and pad surface temperatures are distributed abnormally before the brake failure and the disc pad damage. Therefore, the damage by the failure can be prevented by discovering the abnormality of the machine parts before failure and the life cycle of the pad and the cost can be extended and saved by operating the crane performing constant checkup for the overload.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.96-106
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• 2020

To solve the limitation of traffic monitoring that occur from embedded sensor such as loop and piezo sensors, the thermal imaging camera was installed on the roadside. As the length of Class 1(passenger car) is getting longer, it is becoming difficult to classify from Class 3(2-axle truck) by using an embedded sensor. The collected images were labeled to generate training data. A total of 17,536 vehicle images (640x480 pixels) training data were produced. CNN (Convolutional Neural Network) was used to achieve vehicle classification based on thermal image. Based on the limited data volume and quality, a classification accuracy of 97.7% was achieved. It shows the possibility of traffic monitoring system based on AI. If more learning data is collected in the future, 12-class classification will be possible. Also, AI-based traffic monitoring will be able to classify not only 12-class, but also new various class such as eco-friendly vehicles, vehicle in violation, motorcycles, etc. Which can be used as statistical data for national policy, research, and industry.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.424-431
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• 2002

This paper proposes a new quantitative image assessment model which is essential to verify the performance of block-based DCT coding. The proposed model considers not only global distortions such as frequency sensitivity and channel masking using HVS based visual model, but also distortions including several local distortions caused by block-based coding.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.5
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• pp.341-348
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• 2015

Active infrared thermography methods have been known to possess good fault detection capabilities for the detection of defects in materials compared to the conventional passive thermal infrared imaging techniques. However, the reliability of the technique has been under scrutiny. This paper proposes the lock-in thermography technique for the detection and estimation of artificial subsurface defect size and depth with uncertainty measurement.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.203-208
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• 2015

Image degradation will occur depending on hardware characteristics according to the lapse of time between beam projectors when multivision system is installed in the Theme park/Exhibition/Science Museum. In this paper, we have researched the 10-bit High-depth and high-resolution $360^{\circ}$ projection image analysis technique to solve the problems of quality and the maintenance of the theater. The goal is to minimize the economic losses and the development of special theater calibration system that can efficiently support a quality of an image. We proposed the method of image analysis technology, and explained the detailed functions and evaluation methods for image analysis technique. Evaluation method included the performance items, and proposed reasonable value to the experimental method and the goal value.

• Broadcasting and Media Magazine
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• v.25 no.2
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• pp.7-16
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• 2020

최근 Ultra-High Definition(UHD) 등의 고해상도 디스플레이가 시장에 등장하고 이에 따라 소비자의 요구가 커지면서 기존의 Full-High Definition(FHD)과 같은 저해상도(Low Resolution, LR) 영상을 고해상도(High Resolution, HR) 영상으로 변환할 수 있는 초해상화(Super-Resolution) 알고리즘에 대한 관심이 커지고 있다. 그러나 기존의 전통적인 초해상화 기법들은 고해상도 영상을 복원하는 과정에서 디테일한 부분의 화질 저화 및 열화가 존재하는 것을 확인할 수 있다. 본 논문에서는 이러한 문제를 해결하기 위해 최근 널리 연구되고 있는 딥러닝 기반의 초해상화 알고리즘 연구의 최신 기술 현황 및 동향을 소개하고자 한다. 딥러닝 기반의 초해상화 알고리즘은 기존의 전통적인 기법들에 비해 높은 성능을 보여주고 있으며 현재까지도 다양한 네트워크가 제안되며 활발히 연구되고 있다. 본 논문에서는 딥러닝 기반의 초해상화 알고리즘 중 대표적인 네트워크들을 분석하고 다양한 데이터 셋에 대한 해당 네트워크의 실험 결과를 통해 딥러닝 기반의 초해상화 알고리즘의 우수성을 확인하고자 한다.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.10
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• pp.63-70
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• 2018

Biomedical signal measurement technology using images has been developed, and researches on respiration signal measurement technology for maintaining life have been continuously carried out. The existing technology measured respiratory signals through a thermal imaging camera that measures heat emitted from a person's body. In addition, research was conducted to measure respiration rate by analyzing human chest movement in real time. However, the image processing using the infrared thermal image may be difficult to detect the respiratory organ due to the external environmental factors (temperature change, noise, etc.), and thus the accuracy of the measurement of the respiration rate is low.In this study, the images were acquired using visible light and infrared thermal camera to enhance the area of the respiratory tract. Then, based on the two images, features of the respiratory tract region are extracted through processes such as face recognition and image matching. The pattern of the respiratory signal is classified through the k-nearest neighbor classifier, which is one of the statistical classification methods. The respiration rate was calculated according to the characteristics of the classified patterns and the possibility of breathing rate measurement was verified by analyzing the measured respiration rate with the actual respiration rate.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.5
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• pp.508-515
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• 2011

Bovine incisor was investigated using active infrared thermography(IRT) to visualize crack on bovine teeth. An artificial crack was carefully created in bovine incisor sample by compression load of universal tensile machine. While applying a sinusoidal heat wave to the cracked bovine incisor through halogen lamp, consecutive digital infrared images was captured from the sample surface at a frequency synchronized with heat excitation. Phase information of thermal image was calculated by four-point correlation method and processed to produce the phase image of bovine incisor. This phase image showed clearly the crack on the incisor, which was hardly detected in traditional passive thermography.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1879-1883
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• 2008

본 연구는 자연하천에서의 수온과 유속의 정량적인 관계를 도출하고 이를 검증하기위한 지점별 열화상 촬영 및 분석을 실시하였다. 단계별 연구내용은 다음과 같다. 1)서식처별 수온 모니터링: 수온은 시간 변화에 연동하므로 관측기간 내내 장기간의 모니터링을 실시하였다. 2) 서식처별 유속 관측: 하천에서의 지점별 유속은 강우가 없고 지형변화가 발생하지 않으면 그 차이가 크지 않으므로, 날씨가 좋았던 현장조사 기간 중에는 시간을 고려하지 않은 각 지점별 유속을 취득하였다. 3) 자료 분석: 취득된 수온 자료와 유속 자료를 분석하여 수온과 유속간의 정량적인 상관관계를 규명하였다. 4)분포특성 비교: 대표지점에서의 수치계산 결과와 열화상을 이용하여, 유속과 수온의 면적 분포를 제시하였다. 본 연구에서 제안한 수법을 현업에서 활용하기 위해서는 온도 분포의 주기로 볼 수 있는 1년간의 시기별 조사 및 서식환경이 각각 다른 지점에서의 환경특성을 고려한 분석이 보완되어야만 한다. 하지만 그럼에도 불구하고 적외선 카메라로 촬영한 영상을 이용하여 자연하천에서의 서식지 구분 및 유속 분포를 추정한 본 연구는 향후 그 활용성이 매우 크다고 사료된다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.306-309
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• 2019

The damage to farms due to wild animals such as wild boars and elks increases every year, but, in the current system, the catchers from government hunt animals by using guns at night as making an effort to detect wild animals personally by using flashlights. This is very time-inefficient and immediate follow-up action on being damaged is not possible. In this paper, we introduce a system which can detect and recognize the wild animals or the people with high accuracy using thermal imaging camera and infrared camera in company with deep learning technology, so that could kick out or catch the wild animals more quickly than current system.