• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.1
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• pp.46-55
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• 2006

The purpose of this study is a development of an automatic mosaicing for applying to large number of airborne multispectral images, which reduces manual operation by human. 2436 airborne multispectral images were acquired from DuncanTech MS4100 camera with three bands; green, red and near infrared. LIDAR(LIght Detection And Ranging) data and GPS/INS(global positioning system/inertial navigation system) data were collected with the multispectral images. First, the multispectral images were converted to image patterns by unsupervised classification. Their patterns were compared with those of adjacent images to derive relative spatial position between images. Relative spatial positions were derived for 80% of the whole images. Second, it accomplished an automatic mosaicing using GPS/INS data and unsupervised classification. Since the time of GPS/INS data did not synchronized the time of readout images, synchronized GPS/INS data with the time of readout image were selected in consecutive data by comparing unsupervised classified images. This method realized mosaicing automatically for 96% images and RMSE (root mean square error) for the spatial precision of mosaiced images was only 1.44 m by validation with LIDAR data.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.4
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• pp.70-76
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• 2009

We proposed the device to control a computer mouse with only head movements and eye blinks so that disabilities by car or other accidents can use a computer. The mouse position were estimated from a gyro-sensor which can measure head movements, and the mouse events such as click/double click were from opto sensors which can detect the eyes flicker, respectively. The sensor was mounted on the goggle in order not to disturb the visual field. There was no difference in movement speed between ours and a general mouse, but it required 3$\sim$4 more times in the result of the experiment to evaluate spatial movements and events detection of the proposed mouse because of the low accuracy. We could eliminate cumbersome work to periodically remove the accumulated error and intuitively control the mouse using non-linear relative point method with dead zones. Optical sensors are used in the event detection circuitry designed to remove the influence of the ambient light changes, therefore it was not affected in the change of external light source.

• Journal of the Korean Society of Safety
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• v.28 no.4
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• pp.1-7
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• 2013

Train accidents can be directly connected to fatal accidents-collision, derailment, Fire, railway crossing accidents-resulting in tremendous human casualties. First of all, the railway derailment is not only related to most of railway accidents but also it can lead to much more catastrophic accompanying train overtured than other factors. Therefore, it is most important factor to ensure railway safety. some foreign countries have applied to the detector machines(e.g., ultrasonic detector car, sleep mode, current detector, optical sensing, optical fiber). Since it was developed in order to prevent train from being derailed. In korea, the existing track method has been used to monitor rail condition using track circuit. However, we found out it impossible for Communication Based Train Control system(CBTC), recent technology to detect rail condition using balise(data transmission devices) without no track circuit. For this reason, it is needed instantly to develop real-time monitoring system used to detect broken rails. Firstly, this paper presents domestic and international statues analysis of rail breaks technology. Secondly, the composition and the characteristics of the real-time monitoring system. Finally, the evidence that this system could assumed the location and type of broken rails was proved by the experiment of prototype and operation line tests. We concluded that this system can detect rail break section in which error span exist within${\pm}1m$.

• Journal of Korea Multimedia Society
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• v.9 no.2
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• pp.234-243
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• 2006

The recent rapid development of HCI and surveillance technologies has brought great interests in application systems to process faces. Much of research efforts in these systems has been primarily focused on such areas as face recognition, facial expression analysis and facial feature extraction. However, not many approaches have been reported toward face direction detection. This paper proposes a method to detect the direction of a face using a facial feature called facial triangle, which is formed by two eyebrows and the lower lip. Specifically, based on the single monocular view of the face, the proposed method introduces very simple formulas to estimate the horizontal or vertical rotation angle of the face. The horizontal rotation angle can be calculated by using a ratio between the areas of left and right facial triangles, while the vertical angle can be obtained from a ratio between the base and height of facial triangle. Experimental results showed that our method makes it possible to obtain the horizontal angle within an error tolerance of ${\pm}1.68^{\circ}$, and that it performs better as the magnitude of the vertical rotation angle increases.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.443-449
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• 2022

In this study, in order to improve the disadvantages of the environmental error of the infusion set that performs infusion therapy in the existing clinical practice and to maximize the user's convenience by miniaturizing the existing infusion pump system, the structure of the muscle pump of the human vein was imitated. As a double check valve method, a method for preventing the backflow of fluid and discharging a constant fluid in one direction by external pressure was proposed. The proposed bio-mimic muscle pump uses a check valve that controls the flow of fluid in one direction and a silicone tube with elasticity, and a chamber is constructed. A peristaltic pump for applying intermittent pressure to the tube chamber was constructed using a multi-cam structure roller. In order to verify the performance of the proposed pump, optimization was performed while changing the number of multi-cam rollers and adjusting the speed of the roller driving motor, and the reproducibility of the instantaneous discharge amount and the continuous discharge amount of the pump was compared and tested. The performance of the muscle pump proposed in this study was verified through experiments that it can inject up to 1L of fluid within 12 hours, and that it is possible to inject the fluid with an accuracy of ±0.1ml. Real-time monitoring of the fluid injection volume through the bio-mimic muscle pump proposed in this study not only increases the convenience of the administrator, but also provides a precise fluid administration environment to more patients at a low cost, and additionally applies bubble detection and occlusion detection technology If so, it is believed that a safer medical environment can be provided to patients.

• Journal of the Korea Society for Simulation
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• v.31 no.2
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• pp.11-20
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• 2022

There is a critical need for AI assistance in guard operations of Army base perimeters, which is exacerbated by changes in the national defense and security environment such as force reduction. In addition, the possibility for human error inherent to perimeter guard operations attests to the need for an innovative revamp of current systems. The purpose of this study is to propose a real-time object detection AI tailored to military CCTV surveillance with three unique characteristics. First, training data suitable for situations in which relatively small objects must be recognized is used due to the characteristics of military CCTV. Second, we utilize a data augmentation algorithm suited for military context applied in the data preparation step. Third, a noise reduction algorithm is applied to account for military-specific situations, such as camouflaged targets and unfavorable weather conditions. The proposed system has been field-tested in a real-world setting, and its performance has been verified.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.748-757
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• 2021

In this paper, we propose a gaze estimation network in which eye landmark position detection and gaze direction vector estimation are integrated into one deep learning network. The proposed network uses the Stacked Hourglass Network as a backbone structure and is largely composed of three parts: a landmark detector, a feature map extractor, and a gaze direction estimator. The landmark detector estimates the coordinates of 50 eye landmarks, and the feature map extractor generates a feature map of the eye image for estimating the gaze direction. And the gaze direction estimator estimates the final gaze direction vector by combining each output result. The proposed network was trained using virtual synthetic eye images and landmark coordinate data generated through the UnityEyes dataset, and the MPIIGaze dataset consisting of real human eye images was used for performance evaluation. Through the experiment, the gaze estimation error showed a performance of 3.9, and the estimation speed of the network was 42 FPS (Frames per second).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1853-1858
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• 2021

O-rings fill the gaps between mechanical parts. Until now, the sorting of defective products has been performed visually and manually, so classification errors often occur. Therefore, a camera-based defect classification system without human intervention is required. However, a binarization process is required to separate the required region from the background in the camera input image. In this paper, an adaptive binarization technique that considers the surrounding pixel values is applied to solve the problem that single-threshold binarization is difficult to apply due to factors such as changes in ambient lighting or reflections. In addition, the convex hull technique is also applied to compensate for the missing pixel part. And the learning model to be applied to the separated region applies the residual error-based deep learning neural network model, which is advantageous when the defective characteristic is non-linear. It is suggested that the proposed system through experiments can be applied to the automation of O-ring defect detection.

• Journal of the Korean Institute of Gas
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• v.20 no.5
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• pp.104-111
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• 2016

Recently, the quantities of chemical material are increasing in chemical industries. At that time, release accident is increasing due to aging of equipment, mechanical failure, human error, etc. and industrial complexes found community properties in a specific area. For that matter, chemical release accident can lead to hight probability of large disaster. There is a need to analyze the boundaries optimal sensor placement calculated by selecting release scenarios through release condition and wether condition in a chemical process for release detection and response. This paper is to investigate chlorine release accident scenarios using COMSOL. Through accident scenarios, a numerical calculation is studied to determine optimized sensor placement with weight of detection probability, detection time and concentration. In addition, validity of sensor placement is improved by robustness analysis about unpredicted accident scenarios. Therefore, this verifies our studies can be effectively applicable on any process. As mention above, the result of this study can help to place mobile sensor, to track gas release based concentration data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.19-27
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• 2010

This paper proposes a method for enhancing detection performance and reducing computational cost when detecting a human face by applying B-spline active contour to the frame difference of consecutive images. Firstly, the method estimates amount of user's motion using kurtosis. If the kurtosis is smaller than a pre-defined threshold, it is considered that the amount of user's motion is insufficient and thus the contour fitting is not applied. Otherwise, the contour fitting is applied by exploiting the fact that the amount of motion is sufficient. Secondly, for the contour fitting, difference edges are detected by combining the distance transformation of the binarized frame difference and the edges of current frame. Lastly, the face is located by assigning the contour fitting process to the detected difference edges. Kurtosis-based motion amount estimation can reduce a computational cost and stabilize the results of the contour fitting. In addition, distance transformation-based difference edge detection can enhance the problems of contour lag and discontinuous difference edges. Experimental results confirm that the proposed method can reduce the face localization error caused by the contour lag and discontinuity of edges, and decrease the computational cost by omitting approximately 39% of the contour fitting.