• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.75-77
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• 2021

In order to find objects in an image through deep learning technology, an image dataset for learning is required. In order to increase the recognition rate of objects, a large amount of image learning data is required. It is difficult for individuals to build large amounts of datasets because it is expensive. This paper introduces a method for more easily constructing an image dataset including several sides of an object by photographing a rotating image. A method of constructing a dataset by placing an object on a rotating plate, photographing it, and dividing and synthesizing the captured images according to the needs is proposed.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.3
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• pp.37-43
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• 2004

The purpose of this study is to develop a practical image inspection system that could recognize it correctly, endowing flexibility to the productive field, although the same object for work will be changed in the size and rotated. In this experiment, it selected a fighter, rotating the direction from $30^{\circ}$ to $45^{\circ}$ simultaneously while changing the size from 1/4 to 1/16, as an object inspection without using another hardware for exclusive image processing. The invariant moments, Hu has suggested, was used as feature vector moment descriptor. As a result of the experiment, the image inspection system developed from this research was operated in real-time regardless of the chance of size and rotation for the object inspection, and it maintained the correspondent rates steadily above from 94% to 96%. Accordingly, it is considered as the flexibility can be considerably endowed to the factory automation when the image inspection system developed from this research is applied to the productive field.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.164-169
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• 2003

The purpose of this study is to develop a practical image inspect ion system that could recognize it correctly, endowing flexibility to the productive field, although the same object for work will be changed in the size and rotated. In this experiment, it selected a fighter, rotating the direction from 30$^{\circ}$ to 45 simultaneously while changing the size from 1/4 to 1/16, as an object inspection without using another hardware for exclusive image processing. The invariant moments, Hu has suggested, was used as feature vector moment descriptor. As a result of the experiment, the image inspect ion system developed from this research was operated in real-time regardless of the chance of size and rotation for the object inspection, and it maintained the correspondent rates steadily above from 94％ to 96％. Accordingly, it is considered as the flexibility can be considerably endowed to the factory automat ion when the image inspect ion system developed from this research is applied to the product ive field.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.240-244
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• 2009

In this paper, we present FloatingPad, a touch pad based device with better scrolling feature and more interaction styles than a traditional touch pad. When we interact with a real object like a picture or a book, we manipulate on the object, and we also move, rotate, and flip the object. We applied this idea into a touch pad. In FloatingPad, the touch pad is not fixed to the device. It is floating on the device; it can be slid on the device. Therefore a user can have additional degree of freedom of input by shifting and rotating the touch pad while having the traditional touch pad input. By using this technique, the interactivity of the touch pad can be augmented, and better scrolling feature can be provided by reducing clutching occurs on the position scrolling devices by using the movement of the touch pad as rate control. We implemented the prototype device and conducted a user study with three applications developed for FloatingPad.

• Journal of Korea Multimedia Society
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• v.18 no.1
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• pp.17-24
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• 2015

In this paper, a novel scheme for correcting rotated region in medical images using SIFT(Scale Invariant Feature Transform) algorithm is presented. Using the feature extraction function of SIFT, the rotation angle of rotated object in medical images is calculated as follows. First, keypoints of both reference and rotated medical images are extracted by SIFT. Second, the matching process is performed to the keypoints located at the predetermined ROI(Region Of Interest) at which objects are not cropped or added by rotating the image. Finally, degrees of matched keypoints are calculated and the rotation angle of the rotated object is determined by averaging the difference of the degrees. The simulation results show that the proposed scheme has excellent performance for correcting the rotated region in medical images.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.10
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• pp.1050-1055
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• 2012

The bearing coupling section of machine tools is the most important factor to determine their static/dynamic stiffness. To ensure the proper performance of machine tools, the static/dynamic stiffness of the rotating system has to be predicted on the design stage. Various parameters of the bearing coupling section, such as the spring element, node number and preload influence the characteristics of rotating systems. This study focuses on the prediction of the static and dynamic stiffness of the rotating system with the bearing coupling section using the finite element (FE) model. MATRIX 27 in ANSYS has been adopted to describe the bearing coupling section of machine tools because the MATRIX 27 can describe the bearing coupling section close to the real object and is applicable to various machine tools. The FE model of the bearing couple section which has the sixteen node using MATRIX 27 was constructed. Comparisons between finite element method (FEM) predictions and experimental results were performed in terms of the static and dynamic stiffness.

• Korean Journal of Optics and Photonics
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• v.11 no.4
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• pp.250-254
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• 2000

We have constructed laser Doppler velocimetry system using self-mixing effect with a semiconductor laser. This technology is based on the frequency mixing phenomena which occurs when light scattered back from the moving object into the laser cavity interferes with light inside the laser. We have compared the value of Doppler shifted frequency with the velocity variation of the wheel. Frequency dependence on the angle between the moving direction of rotating aluminum wheel and the incident beam also have been proved. As an illustration of the performance of the velocimeter, velocity measurements of a rotating disk are described. Doppler signal shows a good linear relationship with velocity of rotating disk.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.50 no.3
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• pp.318-325
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• 2014

The main object of this study is to investigate the collection characteristics of wet-type rotating porous disk system experimentally. The experiment is carried out to analyze the pressure drop and collection efficiency for the present system with the experimental parameters such as system inlet velocity, stage number, tube diameter, inlet concentration, etc. In results, for the present system, at 5 stage and ${\upsilon}_{in}=1.8m/s$, the pressure drop becomes significantly lower as $64mmH_2O$ in comparison with that of the conventional wet type scrubber (Venturi scrubber, over $250mmH_2O$). The collection efficiencies increase with higher inlet velocity showing 92, 95.7, 98.4%, while $SO_2$ removal efficiencies decrease with increment of inlet velocity as 80, 65, 50% at ${\upsilon}_{in}=1.08$, 1.44, 1.8 m/s and tube diameter $D_t=10mm$, respectively. The present system is to be considered as an effective compact system for a simultaneous removal of particle/gas phase pollutants from marine diesel engines.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.34-38
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• 2020

In this paper, we implement a Dashcam system capable of shooting 360 degrees using a Raspberry Pi, shock sensors, distance sensors, and rotating camera with a servo motor. If there is an object approaching the vehicle by the distance sensor, the camera rotates to take a video. In the event of an external shock, videos and images are stored in the server to analyze the cause of the vehicle's accident and prevent the user from forging or tampering with videos or images. We also implement functions that transmit the message with the location and the intensity of the impact when the accident occurs and send the vehicle information to an insurance authority with by linking the system with a smart device. It is advantage that the authority analyzes the transmitted message and provides the accident handling information giving the user's safety and convenience.

• The Journal of Korean Institute of Information Technology
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• v.17 no.5
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• pp.13-20
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• 2019

Recently, object detection technology based on CNN has been actively studied. Object detection technology is used as an important technology in autonomous vehicles, intelligent image analysis, and so on. In this paper, we propose a rotation change robust object detection system by applying MI-FL (Moment Invariant-Feature Layer) to SSD (Single Shot Multibox Detector) which is one of CNN-based object detectors. First, the features of the input image are extracted based on the VGG network. Then, a total of six feature layers are applied to generate bounding boxes by predicting the location and type of object. We then use the NMS algorithm to get the bounding box that is the most likely object. Once an object bounding box has been determined, the invariant moment feature of the corresponding region is extracted using MI-FL, and stored and learned in advance. In the detection process, it is possible to detect the rotated image more robust than the conventional method by using the previously stored moment invariant feature information. The performance improvement of about 4 ~ 5% was confirmed by comparing SSD with existing SSD and MI-FL.