• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.959-962
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• 1998

In this paper, we propose an efficient vehicle detection and classification algorithm for an electronic toll collection, which is based on shadow robust vehicle presence test. In order to improve the performance of vehicle presence test, we use correlation coefficients between wavelet transformed input and reference images, which takes advanage of textural similarity. We compare the performance of the vehicle presence test with those of some conventional approaches that use variance of frame difference. Experimental results from field test show that the proposed vehicl detection and classification algorithm performs well even under abrupt intensity change due to the characteristics of sensor and occurrence of shadow.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.449-452
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• 1998

In this study, the basic image-board and algorithm has been developed to extract a road lane by modeling the driving process. The high speed processing enables an image capture, processing and prompt decision making. In order to high speed processing ASIC like FPGA was designed and integrated in one board system. The algorithm enabling road driving must recognize a straight and bend edge separately. The high speed image processing board using FPGA can be used in real-time decision makeing system for road driving and in the machine vision under bad working environments like a coal mine. And it also can be used in the safety control system in subway and in image input system of CCTV and CATV by designing the board to meet various user's needs.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.327-330
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• 2000

In this paper, we describe an intelligent method to detect types of vehicles using Support Vector Machines focused to the Intelligent Transportation System (ITS) applications such as in the CCD based Electronic Toll Collection System (ETCS). This algorithm can be used the various fields of ITS applications. Support Vector Machines employed in this paper has been recently proposed as a very effective method for 3D image recognition. And our proposed feature extraction method using the singluar values that directly come from pixels at input images. Consequently, The low calculation load and the high recognition rate in spite of image rotation and various noises are one of merits of proposed method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.5
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• pp.127-137
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• 1996

In this paper, an algorithm for on-line rightward japanese parsing is proposed. The ambiguity in on-line parsing is accumulated until the input is completely finished, since there is not a space between words in the japanese sentence. Thus the algorithm for morphological analysis, based on modified chart, is used in solving it. And the number of searching a word in dirctionary for morphological analysis is also a puzzling problem. The japanese sentence, consist of N characters, has logically its maximum number of N(N+1)/2 searches in the ordinary on-line analysis, which is nearly twice as many as normal off-line. In this paper, the matter is settled through the modification of dictionary format. In experiment, we can accomplish the rate of analysis which is nearly equal to that of off-line parsing. And it becomes clear that the longer a sentence is, the better an analysis efficiency is.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.5
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• pp.35-44
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• 1997

In this paper, a an algorithm that detects the endocardial boundary, expanding the region from endocardial cavity using fuzzy inference, is proposed. This algorithm decides the ventricular cavity by fuzzy inference in process of searching each pixel from the inside of left ventricle in echocardial image and expands it. Uncertainty and fuzziness exists in decision of endocardial boundary. Therefore, we convert the lingustic representation of mean, standard deviation, and threshold value that are characteristic variables of endocardial boundary to fuzzy input and output variables. And, we extract proposed method is robuster to noise than radial searching method that is highly dependent on center position. To prove the similarity of detected boundary by fuzzy nference, we used the measures of SIZE, correlation coefficient, MSD, and RMSE and had acquired reasonable results.

• Agricultural and Biosystems Engineering
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• v.1 no.1
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• pp.22-29
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• 2000

The development of bio-response feedback control system known as the speaking plant approach has been a challenging task for plant production engineers and scientists. In order to achieve the aim of developing such a bio-response feedback control system, the primary concern should be to develop a practical non-invasive technique for monitoring plant growth. Those who are skilled in raising plants can sense whether their plants are under adequate water conditions or not, for example, by merely observing minor color and tone changes before the plants wilt. Consequently, using machine vision, it may be possible to recognize changes in indices that describe plant conditions based on the appearance of growing plants. The interpretation of image information of plants may be based on image features extracted from the original pictorial image. In this study, the performance of a finite element retina was optimized by a genetic algorithm. The optimized finite element retina was evaluated based on the performance of neural plant growth monitor that requires input data given by the finite element retina.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.3
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• pp.60-68
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• 1994

In this paper, the multiplicative algorithm of two polynomials over finite field GF(($p^{m}$) is presented. Using the presented algorithm, the multiple-valued multiplier of the serial input-output modular structure by CCD is constructed. This multiple-valued multiplier on CCD is consisted of three operation units: the multiplicative operation unit, the modular operation unit, and the primitive irreducible polynomial operation unit. The multiplicative operation unit and the primitive irreducible operation unit are composed of the overflow gate, the inhibit gate and mod(p) adder on CCD. The modular operation unit is constructed by two mod(p) adders which are composed of the addition gate, overflow gate and the inhibit gate on CCD. The multiple-valued multiplier on CCD presented here, is simple and regular for wire routing and possesses the property of modularity. Also. it is expansible for the multiplication of two elements on finite field increasing the degree mand suitable for VLSI implementation.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.11-14
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• 2003

In this paper, we use Fuzzy Logic and Potential field method for optimal path planning of an autonomous mobile robot and apply to navigation for real-time mobile robot in 2D dynamic environment. For safe navigation of the robot, we use both Global and Local path planning. Global path planning is computed off-line using sell-decomposition and Dijkstra algorithm and Local path planning is computed on-line with sensor information using potential field method and Fuzzy Logic. We can get gravitation between two feature points and repulsive force between obstacle and robot through potential field. It is described as a summation of the result of repulsive force between obstacle and robot which is considered as an input through Fuzzy Logic and gravitation to a feature point. With this force, the robot fan get to desired target point safely and fast avoiding obstacles. We Implemented the proposed algorithm with Pioneer-DXE robot in this paper.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.7 s.124
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• pp.662-667
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• 2007

A new neuro-control scheme for active control of structures is proposed. It utilizes lattice pattern of state vector as training data of probabilistic neural network(PNN). Therefore. it is the so-called lattice probabilistic neural network(LPNN). PNN makes control forces by using all the training patterns. Therefore, it takes much time to obtain a control force in application. This inevitably may delay the control action. However. control force of LPNN is calculated by using only the adjacent information of LPNN input. So, the response of LPNN is greatly faster than PNN. The proposed control algorithm is applied for three story building under California and El Centro earthquakes. Also, control results of the LPNN are compared with those of the conventional PNN. The structural responses have been suppressed effectively by the proposed algorithm.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.978-982
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• 2007

A new neuro-control scheme for active control of structures is proposed. It utilizes lattice pattern of state vector as training data of probabilistic neural network (PNN). Therefore, it is the so-called lattice probabilistic neural network (LPNN). PNN makes control forces by using all the training patterns. Therefore, it takes much time to obtain a control force in application. This inevitably may delay the control action. However, control force of LPNN is calculated by using only the adjacent information of LPNN input. So, the response of LPNN is greatly faster than PNN. The proposed control algorithm is applied for one story building under California and El Centro earthquakes. Also, control results of the LPNN are compared with those of the conventional PNN. The structural responses have been suppressed effectively by the proposed algorithm.