• Structural Monitoring and Maintenance
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• 제2권3호
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• pp.181-197
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• 2015

Assessing the condition of paint on civil structures is an important but challenging and costly task, in particular when it comes to large and complex structures. Current practices of visual inspection are labour-intensive and time-consuming to perform. In addition, this task usually relies on the experience and subjective judgment of individual inspectors. In this study, hyperspectral imaging and classification techniques are proposed as a method to objectively assess the state of the paint on a civil or other structure. The ultimate objective of the work is to develop a technology that can provide precise and automatic grading of paint condition and assessment of degradation due to age or environmental factors. Towards this goal, we acquired hyperspectral images of steel surfaces located at long (mid-range) and short distances on the Sydney Harbour Bridge with an Acousto-Optics Tunable filter (AOTF) hyperspectral camera (consisting of 21 bands in the visible spectrum). We trained a multi-class Support Vector Machines (SVM) classifier to automatically assess the grading of the paint from hyperspectral signatures. Our results demonstrate that the classifier generates highly accurate assessment of the paint condition in comparison to the judgement of human experts.

• 로봇학회논문지
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• 제14권1호
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• pp.50-57
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• 2019

This work presents a design and control method for a flexible robot arm operated by a wire drive that follows human gestures. When moving the robot arm to a desired position, the necessary wire moving length is calculated and the motors are rotated accordingly to the length. A robotic arm is composed of a total of two module-formed mechanism similar to real human motion. Two wires are used as a closed loop in one module, and universal joints are attached to each disk to create up, down, left, and right movements. In order to control the motor, the anti-windup PID was applied to limit the sudden change usually caused by accumulated error in the integral control term. In addition, master/slave communication protocol and operation program for linking 6 motors to MYO sensor and IMU sensor output were developed at the same time. This makes it possible to receive the image information of the camera attached to the robot arm and simultaneously send the control command to the robot at high speed.

• 대한조선학회논문집
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• 제56권4호
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• pp.327-334
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• 2019

Recently, there has been a growing interest in artificial supercavitation as a way to reduce friction drag of submerged vehicles. A cavitator plays an important role to generate the supercavity, so many studies have focused on the case of cavitator only. However, the body shape behind the cavitator affects the growth of the supercavity and this effect must be considered for evaluating the overall performance of the system. In this work, we conducted experimental investigation on artificial supercavitation generated by different combinations of the cavitator and body. We observed the supercavity pattern by using a high-speed camera and measured the pressure inside the cavity by using an absolute pressure transducer. We estimated the relation between the amount of injected air and the supercavity shape for different combinations. In summary, the disk type cavitator generates larger supercavity than that of the cone and ellipsoidal cavitators, but cavity development speed is relatively slower rather than the others. Furthermore, fore body angle plays an important role to generate the supercavity enveloping the entire body.

• 전기전자학회논문지
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• 제23권3호
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• pp.978-983
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• 2019

자율주행, AI의 시대가 도래함에 따라 카메라를 통하여 물체를 정확히 인식 및 판단하는 것이 중요해졌다. 특히 카메라를 이용하여 물체를 인식하는 방법은 다른 여러 방법들에 비하여 시각적으로 많은 양의 정보를 얻을 수 있기 때문에 정확한 영상을 추출하기 위하여 많은 영상 신호 처리 방법들이 연구되고 있다. 또한, 이러한 영상 신호 처리의 기능을 실제 하드웨어로 구현하기 위하여 많은 연구도 동시에 진행되고 있다. 본 논문에서는 영상 신호 처리에서 자주 사용되는 정렬 알고리즘에 대하여 동작원리 및 특징을 비교하고 성능에 대한 평가를 정리하였다. 이를 토대로 대표적인 정렬 알고리즘 중 하드웨어로 구현할 때 효율적인 알고리즘에 대하여 정의한다.

• 대한방사선기술학회지:방사선기술과학
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• 제43권6호
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• pp.461-467
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• 2020

In the field of nuclear medicine, errors are sometimes generated because the assessment of the uniformity of gamma cameras relies on the naked eye of the evaluator. To minimize these errors, we created an artificial intelligence model based on CNN algorithm and wanted to assess its usefulness. We produced 20,000 normal images and partial cold region images using Python, and conducted artificial intelligence training with Resnet18 models. The training results showed that accuracy, specificity and sensitivity were 95.01%, 92.30%, and 97.73%, respectively. According to the results of the evaluation of the confusion matrix of artificial intelligence and expert groups, artificial intelligence was accuracy, specificity and sensitivity of 94.00%, 91.50%, and 96.80%, respectively, and expert groups was accuracy, specificity and sensitivity of 69.00%, 64.00%, and 74.00%, respectively. The results showed that artificial intelligence was better than expert groups. In addition, by checking together with the radiological technologist and AI, errors that may occur during the quality control process can be reduced, providing a better examination environment for patients, providing convenience to radiologists, and improving work efficiency.

• Ocean Systems Engineering
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• 제11권4호
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• pp.331-351
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• 2021

Underwater images are very much different from images taken on land, due to the presence of a higher disturbance ratio caused by the presence of water medium between the camera and the target object. These distortions and noises result in unclear details and reduced quality of the output image. An underwater image restoration method is proposed in this paper, which uses blurriness information, background light neutralization information, and red-light intensity to estimate depth. The transmission map is then estimated using the derived depth map, by considering separate attenuation coefficients for direct and backscattered signals. The estimated transmission map and estimated background light are then used to recover the scene radiance. Qualitative and quantitative analysis have been used to compare the performance of the proposed method against other state-of-the-art restoration methods. It has been shown that the proposed method can yield good quality restored underwater images. The proposed method has also been evaluated using different qualitative metrics, and results have shown that method is highly capable of restoring underwater images with different conditions. The results are significant and show the applicability of the proposed method for underwater image restoration work.

• Journal of Information Processing Systems
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• 제18권2호
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• pp.223-234
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• 2022

The evaluation of the print quality of 3D printing has traditionally relied on manual work using dimensional measurements. However, the dimensional measurement method has an error value that depends on the person who measures it. Therefore, we propose the design of a new print quality measurement method that can be automatically measured using the field-of-view (FOV) model and the intersection over union (IoU) technique. First, the height information of the modeling is acquired from a camera; the output is measured by a sensor; and the images of the top and isometric views are acquired from the FOV model. The height information calculates the height ratio by calculating the percentage of modeling and output, and compares the 2D contour of the object on the image using the FOV model. The contour of the object is obtained from the image for 2D contour comparison and the IoU is calculated by comparing the areas of the contour regions. The accuracy of the automated measurement technique for determining, which derives the print quality value was calculated by averaging the IoU value corrected by the measurement error and the height ratio value.

• International Journal of Computer Science & Network Security
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• 제22권12호
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• pp.171-177
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• 2022

The number of people who own indoor plants is growing today, but as a result of their busy lifestyles-such as work or travel-as well as a lack of enthusiasm in caring for their plants, their plants wither. The use of an irrigation control system with a surveillance camera can assist such folks in taking care of their plants. Such a device can assist in remotely watering plants at predetermined times and checking on the health of the plants. The proprietors would be able to live comfortably without feeling bad thanks to this change. Internet access is required for this technology in order to monitor the plants and control the watering through apps. A sensor is installed in the soil to monitor soil humidity and send data to the microcontroller for irrigation, allowing the owner to schedule irrigation as they see fit and keep an eye on their plants all day. With the use of a remote irrigation control system, the plants will grow properly and be irrigated with the proper amount of water, and the owners will be so glad and delighted to watch their plants. Knowing the time and quantity of water are vital parts of the plant growth.

• 한국정밀공학회지
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• 제13권11호
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• pp.64-72
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• 1996

This paper is aimed to develop an optical method for measuring 3-dimensional shapes of specular objects having curved surfaces. The existing methods measuring the shapes of specular objects have several common disadvantages: they may not work properly if the surface is highly specular like mirror surface or if the reflectance property is not uniform over the surface. And, they often require the a priori knowledege about the surface reflectance. To overcome these disadvantages, the measurement using double pass retroreflection method is proposed in this paper. For this measurement principle, an experimental measuring system is designed and prepared which is composed of a galvanometer scanner, a beam splitter, a laser source, a CCD camera, and a reflector made of retroreflective material. To verify the effectiveness of the measurement system a series of experiments are performaed for various specular objects. The results observed from the experiments show that the developed optical sensing system can be an effective mean of measuring the 3-D shapes of specular objects.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2020년도 추계학술발표대회
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• pp.967-970
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• 2020

In a previous work we have done, we presented a monitoring system to automatically detect some dogs' behaviors from videos. However, the input video data used by that system was pre-trimmed to ensure it contained a dog only. In a real-life situation, the monitoring system would continuously receive video data, including frames that are empty and ones that contain people. In this paper, we propose a YOLOv4-based system for automatic object detection and trimming of dog videos. Sequences of frames trimmed from the video data received from the camera are analyzed to detect dogs and people frame by frame using a YOLOv4 model, and then records of the occurrences of dogs and people are generated. The records of each sequence are then analyzed through a rule-based decision tree to classify the sequence, forward it if it contains a dog only or ignore it otherwise. The results of the experiments on long untrimmed videos show that our proposed method manages an excellent detection performance reaching 0.97 in average of precision, recall and f-1 score at a detection rate of approximately 30 fps, guaranteeing with that real-time processing.