• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.293-297
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• 2007

This thesis suggests a new algorithm to detects multiple moving objects using a CMODE(Correct Multiple Object DEtection) method in the color images acquired in real-time and to track the interested pedestrian using motion and hue information. The multiple objects are detected, and then shaking trees or moving cars are removed using structural characteristics and shape information of the man , the interested pedestrian can be detected, The first similarity judgment for tracking an interested pedestrian is to use the distance between the previous interested pedestrian's centroid and the present pedestrian's centroid. For the area where the first similarity is detected, three feature points are calculated using k-mean algorithm, and the second similarity is judged and tracked using the average hue value for the $3{\times}3$ area of each feature point. The zooming of camera is adjusted to track an interested pedestrian at a long distance easily and the FOV(Field of View) of camera is adjusted in case the pedestrian is not situated in the fixed range of the screen. As a experiment results, comparing the suggested CMODE method with the labeling method, an average approach rate is one fourth of labeling method, and an average detecting time is faster three times than labeling method. Even in a complex background, such as the areas where trees are shaking or cars are moving, or the area of shadows, interested pedestrian detection is showed a high detection rate of average 96.5%. The tracking of an interested pedestrian is showed high tracking rate of average 95% using the information of situation and hue, and interested pedestrian can be tracked successively through a camera FOV and zooming adjustment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.590-592
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• 2018

Taxis that are illegally parked on the road to catch customer can cause traffic congestion and sometimes cause traffic accidents. Stop position of taxis is determined by the long term experience of taxi drivers. In this study, We provide information to taxi drivers and customer who visit in first time through finding stop position of taxis by time. To do this, we used the Internet of Vehicle (IoV) data collected from sensors installed in 40 taxis. Previous studies attempted by forming a cluster around a taxi. Since this method is centered on a taxi, the position of the cluster changes depending on the location of the taxi. In this study, we use a road segmentation algorithm to solve these problems. Unlike the previous studies, since the cluster is formed around the road, the position of the cluster is fixed and it is not affected by the number of taxis, so it is possible to grasp the stop position in real time. The road segmentation is made up of 30m units, and map the taxi location data divided into hourly, weekday, and weekend to the nearest point. As a result of the mapping, it was difficult to see a big difference in the time of week because there were few taxis to operate on weekends, but in case of weekdays, the difference of stop position between the commute time zone and the night time zone was confirmed. The results of this study suggest that it will be possible to propose the prevention of taxi illegally driving taxi and the location of the taxi stand.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.3
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• pp.304-315
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• 2001

In this paper, we peformed the real-time implementation of AMR(Adaptive Multi-Rate) speech coding algorithm which is adopted for IMT-2000 service using TMS320C6201, i.e., a Texas Instrument´s fixed-point DSP. With the ANSI C source code released from ETSI, optimization is performed to make it run in real-time with memory as small as possible using the C compiler and assembly language. Implemented AMR speech codec has the size of 32.06 kWords program memory, 9.75 kWords data RAM memory, and 19.89 kWords data ROM memory. And, The time required for processing one frame of 20 ms length speech data is about 4.38 ms, and it is short enough for real-time operation. It is verified that the decoded result of the implemented speech codec on the DSP is identical with the PC simulation result using ANSI C code for test sequences. Also, actual sound input/output test using microphone and speaker demonstrates its proper real-time operation without distortions or delays.

• Journal of Internet Computing and Services
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• v.10 no.2
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• pp.1-13
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• 2009

Intrusion detection is a process that identifies the attacks and responds to the malicious intrusion actions for the protection of the computer and the network resources. Due to the fast development of the Internet, the types of intrusions become more complex recently and need immediate and correct responses because the frequent occurrences of a new intrusion type rise rapidly. Therefore, to solve these problems of the intrusion detection systems, we propose a sequential pattern miner for analysis of the alert data in order to support intelligent and automatic detection of the intrusion. Sequential pattern mining is one of the methods to find the patterns among the extracted items that are frequent in the fixed sequences. We apply the prefixSpan algorithm to find out the alert sequences. This method can be used to predict the actions of the sequential patterns and to create the rules of the intrusions. In this paper, we propose an extended prefixSpan algorithm which is designed to consider the specific characteristics of the alert data. The extended sequential pattern miner will be used as a part of alert data analyzer of intrusion detection systems. By using the created rules from the sequential pattern miner, the HA(high-level alert analyzer) of PEP(policy enforcement point), usually called IDS, performs the prediction of the sequence behaviors and changing patterns that were not visibly checked.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.3
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• pp.43-53
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• 2003

Unlike in analog display devices, the physical screen resolution in digital devices are fixed from the manufacturing. It is a weak point on digital devices. The screen resolution displayed in digital display devices is varied. Thus, interpolation or decimation of the resolution on the display is needed to make the input pixels equal to the screen resolution., This process is called image scaling. Many researches have been developed to reduce the hardware cost and distortion of the image of image scaling algorithm. In this paper, we proposed a Winscale algorithm. which modifies the scale up/down in continuous domain to the scale up/down in discrete domain. Thus, the algorithm is suitable to digital display devices. Hardware implementation of the image scaler is performed using Verilog XL and chip is fabricated in a 0.5${\mu}{\textrm}{m}$ Samsung SOG technology. The hardware costs as well as the scalabilities are compared with the conventional image scaling algorithms that are used in other software. This Winscale algorithm is proved more scalable than other image-scaling algorithm, which has similar H/W cost. This image-scaling algorithm can be used in various digital display devices that need image scaling process.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2291-2297
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• 2015

This paper presents a vehicle detection system using the video as a input image what has moving of vehicles.. Input image has constraints. it has to get fixed view and downward view obliquely from top of the road. Road detection is required to use only the road area in the input image. In introduction, we suggest the experiment result and the critical point of motion history image extraction method, SIFT(Scale_Invariant Feature Transform) algorithm and histogram analysis to detect vehicles. To solve these problem, we propose using applied Gaussian Mixture Model(GMM) that is the Vehicle Detection GMM(VDGMM). In addition, we optimize VDGMM to detect vehicles more and named VDGMM 2.0. In result of experiment, each precision, recall and F1 rate is 9%, 53%, 15% for GMM without road detection and 85%, 77%, 80% for VDGMM2.0 with road detection.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.4
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• pp.737-752
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• 1992

Analysis of elasto-dynamic deformation of flexible linkage mechanism is conducted using the finite element method. The equations of motion of the system are derived from the static structural problem in which dynamic inertia, gravitational and driving forces are treated as external loads. Linear spring model is included in the formulation of equation of motions to represent the effects of deformation of elastic bearings of revolute joints on the system behavior. A computer program is constructed and applied to analyze a specific crank-lever 4-bar mechanism. The algorithm of the program is as follows. First, the natural frequencies and the mode shapes of the system are calculated by solving the eigenproblem of the mechanism system which can be considered as a static structure by assuming the input shaft (crank shaft) to be fixed at any given configuration of mechanism. And finally, the elasto-dynamic deformation of the whole system is obtained using mode superposition method for the case of constant input speed. The effect of geometric stiffness on the mechamism is included in the program with the axial forces of links obtained through the quasi-static displacement analysis. It is found that the geometric stiffness exerts an important effect upon the elasto-dynamic behavior of the flexible linkage mechanism. Elastic deformation of bearing lowers the natural frequencies of the system, resulting smaller elastic displacement at the mid-point of the links and bigger elestic displacement at the ends of the links than rigid bearing. The above investigation of flexible linkage mechanism shows that the effects of the elastic deformation of bearing on the mechanism should be considered to design the mechanism which satisfies more preciously the purpose and the condition of design.

• Journal of Broadcast Engineering
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• v.13 no.4
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• pp.452-462
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• 2008

In this paper, we address issues associated with the real-time implementation of the MPEG-1/2 Layer-II (or MUSICAM) and MPEG-4 ER-BSAC decoders for Digital Multimedia Broadcasting (DMB) on TMS320C64x+ that is a fixed-point DSP processor with a clock speed of 330 MHz. To achieve the real-time requirement, they should be optimized in different steps as follows. First of all, a C-code level optimization is performed by sharing the memory, adjusting data types, and unrolling loops. Next, an algorithm level optimization is carried out such as the reconfiguration of bitstream reading, the modification of synthesis filtering, and the rearrangement of the window coefficients for synthesis filtering. In addition, the C-code of a synthesis filtering module of the MPEG-1/2 Layer-II decoder is rewritten by using the linear assembly programming technique. This is because the synthesis filtering module requires the most processing time among all processing modules of the decoder. In order to show how the real-time implementation works, we obtain the percentage of the processing time for decoding and calculate a RMS value between the decoded audio signals by the reference MPEG decoder and its DSP version implemented in this paper. As a result, it is shown that the percentages of the processing time for the MPEG-1/2 Layer-II and MPEG-4 ER-BSAC decoders occupy less than 3% and 11% of the DSP clock cycles, respectively, and the RMS values of the MPEG-1/2 Layer-II and MPEG-4 ER-BSAC decoders implemented in this paper all satisfy the criterion of -77.01 dB which is defined by the MPEG standards.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.241-241
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• 2012

Semiconductor industry has been taking the advantage of improvements in process technology in order to maintain reduced device geometries and stringent performance specifications. This results in semiconductor manufacturing processes became hundreds in sequence, it is continuously expected to be increased. This may in turn reduce the yield. With a large amount of investment at stake, this motivates tighter process control and fault diagnosis. The continuous improvement in semiconductor industry demands advancements in process control and monitoring to the same degree. Any fault in the process must be detected and classified with a high degree of precision, and it is desired to be diagnosed if possible. The detected abnormality in the system is then classified to locate the source of the variation. The performance of a fault detection system is directly reflected in the yield. Therefore a highly capable fault detection system is always desirable. In this research, time series modeling of the data from an etch equipment has been investigated for the ultimate purpose of fault diagnosis. The tool data consisted of number of different parameters each being recorded at fixed time points. As the data had been collected for a number of runs, it was not synchronized due to variable delays and offsets in data acquisition system and networks. The data was then synchronized using a variant of Dynamic Time Warping (DTW) algorithm. The AutoRegressive Integrated Moving Average (ARIMA) model was then applied on the synchronized data. The ARIMA model combines both the Autoregressive model and the Moving Average model to relate the present value of the time series to its past values. As the new values of parameters are received from the equipment, the model uses them and the previous ones to provide predictions of one step ahead for each parameter. The statistical comparison of these predictions with the actual values, gives us the each parameter's probability of fault, at each time point and (once a run gets finished) for each run. This work will be extended by applying a suitable probability generating function and combining the probabilities of different parameters using Dempster-Shafer Theory (DST). DST provides a way to combine evidence that is available from different sources and gives a joint degree of belief in a hypothesis. This will give us a combined belief of fault in the process with a high precision.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.2
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• pp.138-147
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• 2009

In this paper, improved direct torque control(DTC) system for five-phase squirrel-cage induction motor(IM) is proposed. Due to the additional degrees of freedom, five-phase 1M drives present unique characteristics. Also five-phase motor drives possess many other advantages compared with the traditional three-phase motor drive system, such as reducing an amplitude of torque pulsation and increasing the reliability. The DTC method is advantageous when it is applied to the five-phase IM, because the five-phase inverter provides 32 space vectors in comparison to 8 space voltage vectors into the three-phase inverter. However, five-phase motor has structural drawback of 3rd space-harmonics current component, it is necessary to controlled 3rd harmonic current. So to control 3rd harmonic current and enhance dynamic characteristics of five-phase squirrel-cage IM drive, modified DTC method should be demanded. The characteristics and dynamic performance of traditional five-phase DTC are analyzed and new DTC for five-phase IM is presented. A more precise flux and torque control algorithm for the drives can be suggested and explained For presenting the superior performance of the proposed direct torque control, experimental results are presented using a 32-[bit] fixed point TMS320F2812 digital signal processor with 2.2[kW] induction motor.