• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.308-317
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• 2022

Researches are underway to efficiently reduce the size of video data transmitted and stored in the image analysis process using deep learning-based machine vision technology. MPEG (Moving Picture Expert Group) has newly established a standardization project called VCM (Video Coding for Machine) and is conducting research on video encoding for machines rather than video encoding for humans. We are researching a multitask that performs various tasks with one image input. The proposed pipeline does not perform all object detection of each task that should precede object detection, but precedes it only once and uses the result as an input for each task. In this paper, we propose a pipeline for efficient multitasking and perform comparative experiments on compression efficiency, execution time, and result accuracy of the input image to check the efficiency. As a result of the experiment, the capacity of the input image decreased by more than 97.5%, while the accuracy of the result decreased slightly, confirming the possibility of efficient multitasking.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.718-724
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• 2013

In today's automotive industry, there exist several systems that help drivers reduce the possibility of accidents, such as the ADAS (Advanced Driver Assistance System). The ADAS helps drivers make correct and quick decisions during dangerous situations. This study analyzed the performance of the IMM (Interacting Multiple Model) method based on multiple Kalman filters using the data acquired from a driving simulator. An IMM algorithm is developed to identify the current discrete state of neighboring vehicles using the sensor data and the vehicle dynamics. In particular, the driving modes of the neighboring vehicles are classified by the cruising and maneuvering modes, and the transition between the states is modeled using a Markovian switching coefficient. The performance of the IMM algorithm is analyzed through realistic simulations where a target vehicle executes sudden lane change or acceleration maneuver.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.4
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• pp.399-405
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• 2010

In this paper, the movement faces the problem of the difficult points upon the gaze of the user that corrective action is needed to solve the identification system offers a new perspective. Using the Kalman filter using the position information of the current head position estimated the future. In order to determine the authenticity of the face features of the face structural element information and the processing time is relatively fast horizontal and vertical histogram analysis method to detect the elements of the face. and people grow and infrared bright pupil effect obtained by constructing a real-time pupil detection, tracking and pupil - geulrinteu vectors are extracted.

• Smart Structures and Systems
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• v.19 no.6
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• pp.625-631
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• 2017

In the fields of civil engineering and seismology, it is essential to detect and tracking the vibrations, and the fiber Bragg gratings (FBGs) are typically used as sensors to measure vibrations. Where, one of the most popular and detailed approaches to use FBGs as vibration sensors involves the use of cantilever beam designs, which adds a mass to measure low and moderate frequencies (from 20 Hz up to 1 kHz) with high sensitivities (greater than 10 pm/g). The design consists of a bending strain in the cantilever that is simultaneously transferred to the FBG, resulting in a shift in the wavelength that is proportional to the strain experienced by the cantilever. In this work, we present the experimental results of a vibration sensor design using a cantilever beam to generate an axial uniform strain in the FBG in-line with the vertical axis, which modifies the cantilever's natural frequency that allows the sensor to have a wide frequency broadband without losing sensitivity. This sensor achieved a sensitivity of about 339 pm/g and a natural frequency of 227.3 Hz. The presented design compared with the traditional cantilever beam-based FBG vibration sensors, has the advantages of a simple design for detection on vibration-sensitive structures and its physical parameters can be easily modified in order to satisfy the requirements of the desired vibration measurements.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1487-1495
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• 2013

Time synchronization is a prerequisite in wireless sensor network applications such as object tracking, consistent state update, duplication detection, and temporal order delivery. This paper analyze time synchronization accuracy of pair-wise time synchronization algorithm which is a typical time synchronization model of time synchronization method in wireless sensor networks. In addition, the analyzed results are verified by simulations. These results can be utilized for performance improvement or development of time synchronization in wireless sensor networks.

• Journal of Power Electronics
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• v.15 no.6
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• pp.1547-1558
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• 2015

A predictive functional control (PFC) scheme for permanent magnet synchronous motor (PMSM) servo systems is proposed in this paper. The PFC-based method is first introduced in the control design of speed loop. Since the accuracy of the PFC model is influenced by external disturbances and speed detection quantization errors of the low distinguishability optical encoder in servo systems, it is noted that the standard PFC method does not achieve satisfactory results in the presence of strong disturbances. This paper adopted the Kalman filter to observe the load torque, the rotor position and the rotor angular velocity under the condition of a limited precision encoder. The observations are then fed back into PFC model to rebuild it when considering the influence of perturbation. Therefore, an improved PFC method, called the PFC+Kalman filter method, is presented, and a high performance PMSM servo system was achieved. The validity of the proposed controller was tested via experiments. Excellent results were obtained with respect to the speed trajectory tracking, stability, and disturbance rejection.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.246-252
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• 2020

Facial recognition is a biometric technology that is used in various fields such as user authentication and identification of human characteristics. Face recognition applications are practically used in various fields, but very few applications have been developed to improve the factory work environment. We implemented applications that uses face recognition to identify a specific employee in a factory .work environment and provide customized information for each employee. Factory workers need documents describing the work in order to do their assigned work. Factory managers can use our application to register documents needed for each worker, and workers can view the documents assigned to them. Each worker is identified using face recognition, and by tracking the worker's face during work, it is possible to know that the worker is in the workplace. In addition, as a mobile app for workers is provided, workers can view the contents using a tablet, and we have defined a simple communication protocol to exchange information between our applications. We demonstrated the applications in a factory work environment and found several improvements were required for practical use. We expect these results can be used to improve factory work environments.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.1
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• pp.78-87
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• 1989

In this paper, a spatio-temporal gradient (STG) method with generalized least square estimation (GLSE) is proposed for the detection of an object motion in an image sequence corrupted by white Gaussian noise. The proposed method is applied to an automatic target tracker using a high speed 16-bit microprocessor in order to track one moving target in real time. Experimental results show that the proposed method has much better performance over the conventional one with least square estimation (LSE).

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.3
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• pp.331-338
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• 2016

In this paper, we propose a GRNN(: Generalized Regression Neural Network) algorithms for new eyes and face recognition identification system to solve the points that need corrective action in accordance with the existing problems of facial movements gaze upon it difficult to identify the user and. Using a Kalman filter structural information elements of a face feature to determine the authenticity of the face was estimated future location using the location information of the current head and the treatment time is relatively fast horizontal and vertical elements of the face using a histogram analysis the detected. And the light obtained by configuring the infrared illuminator pupil effects in real-time detection of the pupil, the pupil tracking was - to extract the text print vector.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2046-2052
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• 2016

Ramp metering is one of the most efficient and widely used control methods for an intelligent transportation management system on a freeway. Its objective is to control and upgrade freeway traffic by regulating the number of vehicles entering the freeway entrance ramp, in such a way that not only the alleviation of the congestion but also the smoothing of the traffic flow around the desired density level can be achieved for the maintenance of the maximum mainline throughput. When the cycle of the signal detection is larger than that of the system process, the density tracking problem needs to be considered in the form of the discrete-time system. Therefore, a discrete-time sliding mode control method is proposed for the ramp metering problem in the presence of both input constraint in the on-ramp and exogenous disturbance in the off-ramp considering the random behavior of the driver. Simulations were performed using a validated second-order macroscopic traffic flow model in Matlab environment and the simulation results indicate that proposed control method can achieve better performance than previously well-known ALINEA strategy in the sense that mainstream flow throughput is maximized and congestion is alleviated even in the presence of input constraint and exogenous disturbance.