• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.320-326
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• 2021

AVTE(Air Vehicle Test Equipment) is an equipment to inspect and check the status of on-board aircraft LRUs(Line Replacement Units) before and after flight for performing successful UAV(Unmanned Aerial Vehicle) missions. This paper suggests utilization of the AVTE as an operation support-equipment by implementing several critical functions for UAV-operation on the AVTE. The AVTE easily sets initialization(default) data and compensates for the installation and position errors of the LRUs which provide critical mission data and situation image with pilots without additional individual operation support-equipment. Major fault list and situation image data could be downloaded after flight using the AVTE in the event of UAV emergency situation or unusual occurrence on duty as well. We anticipate the suggested operational approach of the AVTE could dramatically reduce the cost and man power for design and manufacture of additional operation support equipment and effectively diminish workload of the operator.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.77-84
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• 2022

In this paper, we propose a Label Reassignment Strategy to improve the performance of an object detection algorithm. Our approach involves two stages: an inference stage and an assignment stage. In the inference stage, we perform multi-scale inference with predefined scale sizes on a trained model and re-infer masked images to obtain robust classification results. In the assignment stage, we calculate the IoU between bounding boxes to remove duplicates. We also check box and class occurrence between the detection result and annotation label to re-assign the dominant class type. We trained the YOLOX-L model with the re-annotated dataset to validate our strategy. The model achieved a 3.9% improvement in mAP and 3x better performance on AP_S compared to the model trained with the original dataset. Our results demonstrate that the proposed Label Reassignment Strategy can effectively improve the performance of an object detection model.

• Journal of Korea Water Resources Association
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• v.53 no.10
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• pp.845-859
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• 2020

Climate change and recent heat waves have drawn public attention toward other environmental issues, such as water pollution in the form of algal blooms, chemical leaks, and oil spills. Water pollution by the leakage of chemicals may severely affect human health as well as contaminate the air, water, and soil and cause discoloration or death of crops that come in contact with these chemicals. Chemicals that may spill into water streams are often colorless and water-soluble, which makes it difficult to determine whether the water is polluted using the naked eye. When a chemical spill occurs, it is usually detected through a simple contact detection device by installing sensors at locations where leakage is likely to occur. The drawback with the approach using contact detection sensors is that it relies heavily on the skill of field workers. Moreover, these sensors are installed at a limited number of locations, so spill detection is not possible in areas where they are not installed. Recently hyperspectral images have been used to identify land cover and vegetation and to determine water quality by analyzing the inherent spectral characteristics of these materials. While hyperspectral sensors can potentially be used to detect chemical substances, there is currently a lack of research on the detection of chemicals in water streams using hyperspectral sensors. Therefore, this study utilized remote sensing techniques and the latest sensor technology to overcome the limitations of contact detection technology in detecting the leakage of hazardous chemical into aquatic systems. In this study, we aimed to determine whether 18 types of hazardous chemicals could be individually classified using hyperspectral image. To this end, we obtained hyperspectral images of each chemical to establish a spectral library. We expect that future studies will expand the spectral library database for hazardous chemicals and that verification of its application in water streams will be conducted so that it can be applied to real-time monitoring to facilitate rapid detection and response when a chemical spill has occurred.

• Journal of radiological science and technology
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• v.30 no.2
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• pp.113-119
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• 2007

It is important to consider the contrast of object in Mammography because an absorption gap between tissues of body and breast in breast is low. This study is to evaluate MTF image with resolution chart according to change of combination of target and filter. The results were as follows : 1. There were significant differences in X-ray energy according to combination of filter(Mo/Mo, Mo/Rh. Mo/Al, Rh/Rh, Rh/Al) and acrylic thickness(2 cm, 3 cm, 4 cm). 2. The value of lp/mm on MTF to 0.5 showed that the sharpness in MTF curve was 2.4 compared to Mo/Mo and 2cm acryl, 2.63 in Mo/Rh and 4 cm acryl, and 2.9 in Rh/Rh and 6cm acryl. 3. The value of lp/mm on MTF showed that the resolution in MTF curve was 6.0 compared to Mo/Mo and 2 cm acryl, 4.60 in Rh/Al and 4cm acryl, and 6.03 in Rh/Al and 6 cm acryl. 4. The value of MTF on 2.5 lp/mm distinguishable visually was 0.48 compared to Mo/Mo and 2 cm acryl, 0.53 in Mo/Rh and 4cm acryl, and 0.59 in Rh/Rh and 6cm acryl. 5. For the evaluation of an image of the mammo-phantom, the score of Mo/Mo was 12 points, Mo/Rh 11, Rh/Rh 10.5, Mo/Al 10, Rh/Al 9.0, respectively.

• Progress in Medical Physics
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• v.26 no.1
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• pp.52-58
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• 2015

The automated dental cavity detection program for a new concept intra-oral dental x-ray imaging device, an auxiliary diagnosis system, which is able to assist a dentist to identify dental caries in an early stage and to make an accurate diagnosis, was to be developed. The primary theory of the automatic dental cavity detection program is divided into two algorithms; one is an image segmentation skill to discriminate between a dental cavity and a normal tooth and the other is a computational method to analyze feature of an tooth image and take an advantage of it for detection of dental cavities. In the present study, it is, first, evaluated how accurately the DRLSE (Direct Regularized Level Set Evolution) method extracts demarcation surrounding the dental cavity. In order to evaluate the ability of the developed algorithm to automatically detect dental cavities, 7 tooth phantoms from incisor to molar were fabricated which contained a various form of cavities. Then, dental cavities in the tooth phantom images were analyzed with the developed algorithm. Except for two cavities whose contours were identified partially, the contours of 12 cavities were correctly discriminated by the automated dental caries detection program, which, consequently, proved the practical feasibility of the automatic dental lesion detection algorithm. However, an efficient and enhanced algorithm is required for its application to the actual dental diagnosis since shapes or conditions of the dental caries are different between individuals and complicated. In the future, the automatic dental cavity detection system will be improved adding pattern recognition or machine learning based algorithm which can deal with information of tooth status.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.7-12
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• 2012

Recently the medical field to efficiently process the vast amounts of information to decision trees, neural networks, Bayesian Networks, including the application method of various data mining techniques are investigated. In addition, the basic personal information or patient history, family history, in addition to information such as MRI, HRCT images and additional information to collect and leverage in the diagnosis of disease, improved diagnostic accuracy is to promote a common status. But in real world situations that affect the results much because of the variable exists for a particular data mining techniques to obtain information through the enemy can be seen fairly limited. Medical images were taken as well as a minor can not give a positive impact on the diagnosis, but the proportion increased subjective judgments by the automated system is to deal with difficult issues. As a result of a complex reality, the situation is more advantageous to deal with the relative probability of the multivariate model based on Bayesian network, or TAN in the K2 search algorithm improves due to expansion model has been proposed. At this point, depending on the type of search algorithm applied significantly influenced the performance characteristics of the extended Bayesian network, the performance and suitability of each technique for evaluation of the facts is required. In this paper, we extend the Bayesian network for diagnosis of diseases using the same data were carried out, K2, TAN and changes in search algorithms such as classification accuracy was measured. In the 10-fold cross-validation experiment was performed to compare the performance evaluation based on the analysis and the onset of high-risk classification for patients with HRCT images could be possible to identify high-risk data.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.557-560
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• 2006

최근 들어 정보통신 분야의 기술이 급격히 발전함에 따라 컴퓨터 사용의 증가와 임베디드 시스템 및 사회 각 분야에서 보안에 대한 의식이 점점 높아져 가고 있다. 각 분야에서 신체 정보를 이용한 연구들이 활발히 이루어지고 있는데 본 논문에서는 USB 캠을 이용한 실시간 얼굴 인식 방법에 대해서 제안한다. 카메라를 이용하여 얼굴을 인식하는 방법은 현재까지 여러 가지 방법들이 제시되어 왔지만 일반 pc에서 쓰는 USB 캠을 사용하여 제약 조건 없고 안정적인 인식 방법은 아직까지 나와 있지 않다. 얼굴영역을 주성분 변수로 변환하여 영상의 명암, 얼굴위치, 얼굴의 영역을 추출할 수 있는 기존의 시스템들이 많이 연구되어 왔는데 본 논문에서 제안된 방법에서는 일상생활에서 흔히 쓰는 USB 캠을 사용하여 기존의 CCTV와 같은 고가의 하드웨어를 대체하며 보다 효율적인 성능을 위하여 얼굴을 식별하기 위해 LVQ, FCMA, RBF 알고리즘을 적용한 시스템을 설계한다.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.05a
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• pp.193-199
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• 2002

Analyzing working conditions with shape characteristics of wear debris in a lubricated machine, it can be effect on diagnosis of hydraulic machining system. And it can be recognized that results are processed threshold images of wear debris. But, in order to predict and estimate a working condition of lubricated machine, it is need to analysis a shape characteristic of wear debris and to identify. Therefor, If shape characteristics of wear debris are identified by computer image analysis and the neural network, it is possible to find the cause and effect of wear condition. In this stud)r, wear debris in the lubricant oil are extracted by membrane filter $(0.45{\mu}m)$, and the quantitative value of shape characteristic of wear debris are calculated by the digital image processing. This morphological information are studied and identified by tile artificial neural network. The purpose of this study is to apply morphological characteristic of wear debris to prediction and estimation of working condition in hydraulic machining systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.833-838
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• 2003

This paper presents novel methods of recognizing license plates of passing vehicles outdo(n. In particular, the proposed method is much robust for inclined plates caused by the changes of camera placement. To acquire fine images of quickly passing vehicles under a wide range of illumination conditions, we developed a sensing system having superb characteristics. We expanded the dynamic range and eliminated the blurring of images of fast moving vehicles by synthesizing a pair of synchronized images with different intensities. furthermore, to extend the flexibility of the positioning of the TV camera, we propose a recognition algorithm that can be applied to inclined plates. The performance of the integrated system was investigated on real images of vehicles captured under various illumination conditions. The recognition rates of over 99% (conventional plates) and over 97% (highly inclined plates) shows that the developed system is effective for license plate recognition.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.486-489
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• 2011

본 논문에서는 위성 DMB 환경에서 멀티채널 오디오 서비스를 제공할 수 있는 시스템을 제안한다. 위성 DMB 서비스는 2005 년부터 상용서비스를 시작한 이동멀티미디어방송 서비스로서, QVGA 급의 영상과 FM 음질의 오디오 서비스를 제공한다. 본 연구에서는 기존의 위성 DMB 시스템과 호환성을 유지하면서, 적은 비트율의 데이터를 추가하여 멀티채널 오디오 서비스를 제공하는 시스템에 대한 연구를 수행하였다. 이를 위하여 기존의 스테레오 오디오 시스템과 호환성을 가지면서도 적은 비트율의 데이터 추가만으로 멀티채널 오디오 신호의 재현이 가능한 멀티채널 오디오 부호화 기술을 적용하였고, 기존 위성 DMB 단말의 동작에 영향을 주지 않으면서, 멀티채널 오디오 서비스가 제공되는 것을 식별할 수 있도록 하는 시그널링 방법을 개발하여 적용하였다. 연구 결과의 검증을 위하여 위성 DMB 멀티채널 오디오 부호화기 및 단말을 개발하여 방송 실험을 수행하였고, 이를 통하여 제안한 방법으로 위성 DMB 환경에서 멀티채널 오디오 서비스를 효율적으로 제공할 수 있음을 증명하였다.