• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.7
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• pp.1126-1132
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• 2002

In this paper, we propose a new scheme of motion tracking based on fuzzy inference (Fl) and wavelet transform (WT) from image sequences. First, we present a WT to segment a feature extraction of dynamic image . The coefficient matrix for 2-level DWT tent to be clustered around the location of Important features in the images, such as edge discontinuities, peaks, and corners. But these features are time varying owing to the environment conditions. Second, to reduce the spatio-temperal error, We develop a fuzzy inference algorithm. Some experiments are performed 0 testify the validity and applicability of the proposed system As a result, proposed method is relatively simple compared with the traditional space domain method. It is also well suited for motion tracking under the conditions of variation of illumination.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.1
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• pp.16-26
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• 1998

The major effective factors on the ride quality of a vehicle are the vibration and noise of the engine and drive system. Engine contributes about 80% of the vibration and noise in the vehicle, and exciting forces of the engine are transmitted onto the vehicle frame through the engine mount. This paper studies the vibration reduction of a vehicle through the improvement of the engine mount. A computer program for optimal design is developed and the engine mount conditions are optimized to reduce the WRMS of PSD of acceleration at the driver's seat, which are caused by the exciting forces at the idle speed. Design variables are selected as the stiffness, mount angle and the location of the engine mount rubber. It is shown through computer simulation that the PSD of acceleration at the driver's seat can be improved by redesigning the engine mount system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.430-434
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• 2001

Virtual manufacturing system is integrated computer model that represents the precise and whole structure of manufacturing system and simulates its physical and logical behavior in operation.[1] A virtual machine is computer model that represents a CNC machine tool and one of core elements of virtual manufacturing system. In this paper, it is emphasized that a virtual machine must be web-based system for serving information to all attendants in a real machine tool without the restriction of time or location, and then in the fault diagnosis, one of important modules of a virtual machine, the methods of both using the controller signal and web-based expert system are proposed.

• Journal of the Korean Society of Combustion
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• v.20 no.4
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• pp.1-9
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• 2015

The object of this study is a deriving the relations according to the measuring locations between the chemiluminescence and the flame state at commercial burner. In this study, the flame chemiluminescence of the flame of commercial burner is measured using a photomultiplier tube and the optical band-pass filter. In addition, the contour of the chemiluminescence of the flame is measured using the common CCD camera and the optical band-pass filters, and the acquired images is converted by the simple image processing as a matrix form. The results showed that certain relationship between optical data and equivalence ratio exists, and the contour according to the measuring location of the flame chemiluminescence is different by equivalence ratio.

• Journal of the Optical Society of Korea
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• v.19 no.2
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• pp.144-148
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• 2015

An alternative description for the Gaussian image plane (GIP) of an optical system for a given object is presented, which applies to both aberration-free and non-aberration-free systems. We extend the definition of transverse magnification (TM) to the image plane (IP) displaced from the GIP and find that the TM depends linearly on the locations of both an aperture stop placed in front of the system and the IP. Hence, we redefine the GIP as the location at which the slope of the TM variance changes sign. The definition is deterministic and self-consistent and, therefore, no other parameters or measurements are needed. The derivation of this definition using a set of paraxial ray tracings and supporting experimental data for a thick bi-convex lens system is presented.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.11a
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• pp.55-56
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• 2020

The construction industry has the highest occupational fatality and injury rates related to accidents of any industry. Accordingly, safety managers closely monitor to prevent accidents in real-time by installing surveillance cameras at construction sites. However, due to human cognitive ability limitations, it is impossible to monitor many videos simultaneously, and the fatigue of the person monitoring surveillance cameras is also very high. Thus, to help safety managers monitor work and reduce the occupational accident rate, a study on object recognition in construction sites was conducted through surveillance cameras. In this study, we applied to the instance segmentation to identify the classification and location of objects and extract the size and shape of objects in construction sites. This research considers ways in which deep learning-based computer vision technology can be applied to safety management on a construction site.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.33-38
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• 2024

In this paper, we propose the implementation of a drone delivery system using artificial intelligence in a situation where the use of drones is rapidly increasing and human errors are occurring. This system requires the implementation of an accurate control algorithm, assuming that last-mile delivery is delivered to the apartment veranda. To recognize the delivery location, a recognition system using the YOLO algorithm was implemented, and a delivery system was installed on the drone to measure the distance to the object and increase the delivery distance to ensure stable delivery even at long distances. As a result of the experiment, it was confirmed that the recognition system recognized the marker with a match rate of more than 60% at a distance of less than 10m while the drone hovered stably. In addition, the drone carrying a 500g package was able to withstand the torque applied as the rail lengthened, extending to 1.5m and then stably placing the package down on the veranda at the end of the rail.

• Journal of the Ergonomics Society of Korea
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• v.4 no.1
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• pp.11-16
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• 1985

The object of this research is to develop an Interactive Computerized Graphic Program for graphic output of velocity, acceleration and motion range of body-task reference point (e.g., C.O.G., joint location, etc.). Human motions can be reproduced by scanning (rate = 60Hz) the vidicon image, and the results are stored in an Apple II P.C. memory. The results of this study can be extended to simulation and reproduction of human motions for optimal task design.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.1
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• pp.1-16
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• 1998

The zone clustering problem arising from several area such as deciding the optimal location of ambient measuring stations is to devide the 2-dimensional area into several sub areas in which included individual zone shows simimlar properties. In general, the optimal solution of this problem is very hard to obtain. Therefore, instead of finding an optimal solution, the generation of near optimal solution within the limited time is more meaningful. In this study, the combination of a genetic algorithm and the modified k-means method is used to obtain the near optimal solution. To exploit the genetic algorithm effectively, a representation of chromsomes and appropriate genetic operators are proposed. The k-means method which is originally devised to solve the object clustering problem is modified to improve the solutions obtained from the genetic algorithm. The experiment shows that the proposed method generates the near optimal solution efficiently.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2337-2341
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• 2005

This paper presents the target detection method using Support Vector Machines(SVMs) and the navigation system using behavior-based fuzzy controller. SVM is a machine-learning method based on the principle of structural risk minimization, which performs well when applied to data outside the training set. We formulate detection of target objects as a supervised-learning problem and apply SVM to detect at each location in the image whether a target object is present or not. The behavior-based fuzzy controller is implemented as an individual priority behavior: the highest level behavior is target-seeking, the middle level behavior is obstacle-avoidance, the lowest level is an emergency behavior. We have implemented and tested the proposed method in our mobile robot "Pioneer2-AT". Comparing with a neural-network based detection method, a SVM illustrate the excellence of the proposed method.