• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.3
• /
• pp.697-705
• /
• 2014

This paper presents a vision based object width measurement method and its application where the light sectioning method is employed. The target object for measurement is a tread, which is the most outside component of an automobile tire. The entire system applying the measurement method consists of two processes, i.e. a calibration process and a detection process. The calibration process is to identify the relationships between a camera plane and a laser plane, and to estimate a camera lens distortion parameters. As the process requires a test pattern, namely a jig, which is elaborately manufactured. In the detection process, first of all, the region that a laser light illuminates is extracted by applying an adaptive thresholding technique where the distribution of the pixel brightness is considered to decide the optimal threshold. Then, a thinning algorithm is applied to the region so that the ends and the shoulders of a tread are detected. Finally, the tread width and the shoulder width are computed using the homography and the distortion coefficients obtained by the calibration process.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.7 no.1
• /
• pp.81-90
• /
• 2002

This paper presents an Implementation of digital high-performance position sensorless control system of Reluctance Synchronous Motor(RSM) drives with Direct Torque Control(DTC). The system consists of stator flux observer, speed and torque estimator, two digital hysteresis controllers, an optimal switching look-up table, Insulated Gate Bipolar Transistor(IGBT) voltage source inverter, and TMS320C31 DSP board. The stator flux observer Is based on the combined voltage and current model with stator flux feedback adaptive control of which inputs are current and voltage sensed on motor terminal for wide speed range. In order to prove the suggested sensorless control algorithm for industrial field application, we have some simulation and actual experiment at low and high speed range. The developed high-performance speed control by fully digital system are shown a good response characteristic of control results and high performance features using 1.0[kW] RSM having 2.57 reluctance ratio of $L_d/L_q$.

• The KIPS Transactions:PartC
• /
• v.9C no.1
• /
• pp.65-72
• /
• 2002

In this paper, we implement a high-speed swatch tilth the function for label integration to enhance the expansion of networks using the label space of routers efficiently on MPLS over ATM networks. We propose an appropriate hardware structure to support the VC-merge function and differentiated services simultaneously. In this paper, we use the adaptive congestion control method such as EPD algorithm in carte that there is a possibility of network congestion in output buffers of each core LSR. In addition, we justify the validity of the proposed VC-merge method through simulation and comparison to conventional Non VC-merge methods. The proposed VC-merge capable switch is modeled in VHDL. synthesized, and fabricated using the SAMSUNG 0.5um SOG process.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.9
• /
• pp.2129-2137
• /
• 2015

Lots of research and development works have been actively focused on the self-driving vehicles, locally and globally. In order to implement the self-driving vehicles, lots of fundamental core technologies need to be successfully developed and, specially, it is noted that traffic lights detection and recognition system is an essential part of the computer vision technologies in the self-driving vehicles. Up to nowadays, most conventional algorithm for detecting and recognizing traffic lights are mainly based on the color signal analysis, but these approaches have limits on the performance improvements that can be achieved due to the color signal noises and environmental situations. In order to overcome the performance limits, this paper introduces the morphological analysis for the traffic lights recognition. That is, by considering the color component analysis and the shape analysis such as rectangles and circles simultaneously, the efficiency of the traffic lights recognitions can be greatly increased. Through several simulations, it is shown that the proposed method can highly improve the recognition rate as well as the mis-recognition rate.

• Journal of Sensor Science and Technology
• /
• v.21 no.2
• /
• pp.144-150
• /
• 2012

A microphone for fully implantable hearing device was generally implanted under the skin of the temporal bone. So, the implanted microphone's characteristics can be affected by the accompanying noise due to masticatory movement. In this paper, the implantable microphone with 2-channels structure was designed for reduction of the generated noise signal by masticatory movement. And an experimental model for generation of the noise by masticatory movement was developed with considering the characteristics of human temporal bone and skin. Using the model, the speech signal by a speaker and the artificial noise by a vibrator were supplied simultaneously into the experimental model, the electrical signals were measured at the proposed microphone. The collected signals were processed using a general adaptive filter with least mean square(LMS) algorithm. To confirm performance of the proposed methods, the correlation coefficient and the signal to noise ratio(SNR) before and after the signal processing were calculated. Finally, the results were compared each other.

• Industrial Engineering and Management Systems
• /
• v.4 no.1
• /
• pp.54-67
• /
• 2005

This paper provides an evaluation of an optimization-based, multiple-input double-output (MIDO) run-to-run (R2R) control scheme for general semiconductor manufacturing processes. The controller in this research, termed adaptive dual response optimizing controller (ADROC), can serve as a process optimizer as well as a recipe regulator between consecutive runs of wafer fabrication. In evaluation, it is assumed that the equipment model could be appropriately described by a pair of second-order polynomial functions in terms of a set of controllable variables. Of practical relevance is to consider a drifting effect in the equipment model since in common semiconductor practice the process tends to drift due to machine aging and tool wearing. We select a typical application of R2R control to chemical mechanical planarization (CMP) in semiconductor manufacturing in this evaluation, and there are five different CMP process scenarios demonstrated, including mean shift, variance increase, and IMA disturbances. For the controller, ADROC, an on-line estimation technique is implemented in a self-tuning (ST) control manner for the adaptation purpose. Subsequently, an ad hoc global optimization algorithm based on the dual response approach, arising from the response surface methodology (RSM) literature, is used to seek the optimum recipe within the acceptability region for the execution of next run. The main components of ADROC are described and its control performance is assessed. It reveals from the evaluation that ADROC can provide excellent control actions for the MIDO R2R situations even though the process exhibits complicated, nonlinear interaction effects between control variables, and the drifting disturbances.

• Journal of the Institute of Convergence Signal Processing
• /
• v.6 no.1
• /
• pp.15-22
• /
• 2005

In this paper, we propose a face recognition system by using the CCD color image. We first get the face candidate image by using YCbCr color model and adaptive skin color information. And we use it initial curve of active contour model to extract face region. We use the Eye map and mouth map using color information for extracting facial feature from the face image. To obtain center point of Log-polar image, we use extracted facial feature from the face image. In order to obtain feature vectors, we use extracted coefficients from DCT and wavelet transform. To show the validity of the proposed method, we performed a face recognition using neural network with BP learning algorithm. Experimental results show that the proposed method is robuster with higher recogntion rate than the conventional method for the rotation and scale variant.

• Journal of Power Electronics
• /
• v.18 no.1
• /
• pp.234-250
• /
• 2018

This paper presents a new load sharing control for use between paralleled three-phase inverters in an islanded microgrid based on the online line impedance estimation by the use of a Kalman filter. In this study, the mismatch of power sharing when the line impedance changes due to temperature, frequency, significant differences in line parameters and the requirements of the Plug-and-Play mode for inverters connected to a microgrid has been solved. In addition, this paper also presents a new droop control method working with the line impedance that is different from the traditional droop algorithm when the line impedance is assumed to be pure resistance or pure inductance. In this paper, the line impedance estimation for parallel inverters uses the minimum square method combined with a Kalman filter. In addition, the secondary control loops are designed to restore the voltage amplitude and frequency of a microgrid by using a combined nominal value SOGI-PLL with a generalized integral block and phase lock loop to monitor the exact voltage magnitude and frequency phase at the PCC. A control model has been simulated in Matlab/Simulink with three voltage source inverters connected in parallel for different ratios of power sharing. The simulation results demonstrate the accuracy of the proposed control method.

• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.10
• /
• pp.955-961
• /
• 2010

In this paper, we describe a study of a vehicle detection method based on a Boosting Classifier which uses Histogram of Oriented Gradient (HOG) features and Image Segmentation techniques. An input image is segmented by means of a split and merge algorithm. Then, the two largest segmented regions are removed in order to reduce the search region and speed up processing time. The HOG features are then calculated for each pixel in the search region. In order to detect the vehicle region we used the AdaBoost (adaptive boost) method, which is well known for classifying samples with two classes. To evaluate the performance of the proposed method, 537 training images were used to train and learn the classifier, followed by 500 non-training images to provide the recognition rate. From these experiments we were able to detect the proper image 98.34% of the time for the 500 non-training images. In conclusion, the proposed method can be used for detecting the location of a vehicle in an intelligent vehicle control system.

• Journal of Intelligence and Information Systems
• /
• v.13 no.4
• /
• pp.91-104
• /
• 2007

Ontology matching technique is one of the most important techniques in the Semantic Web as well as in other areas. Ontology matching algorithm takes two ontologies as input, and finds out the matching relations between the two ontologies by using some parameters in the matching process. Ontology matching is very useful in various areas such as the integration of large-scale ontologies, the implementation of intelligent unified search, and the share of domain knowledge for various applications. In general cases, the performance of ontology matching is estimated by measuring the matching results such as precision and recall regardless of the requirements that came from the matching environment. Therefore, most research focuses on controlling parameters for the optimization of precision and recall separately. In this paper, we focused on the harmony of precision and recall rather than independent performance of each. The purpose of this paper is to propose a methodology that determines parameters for the desired ratio of precision and recall that is appropriate for the requirements of the matching environment.