• Journal of Korea Multimedia Society
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• v.7 no.1
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• pp.35-43
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• 2004

In this paper, we proposed a vehicle recognition and electronic toll collection system with detection and classification of vehicle identification mark and emblem as well as recognition of vehicle license plate to unman toll fee collection system or incoming/outcoming vehicles to an institution. In the proposed algorithm, we first process pre-processing step such as noise reduction and thinning from the rear side input image of vehicle and detect vehicle mark, emblem and license plate region using intensity variation informations, template masking and labeling operation. And then, we classify the detected vehicle features regions into vehicle mark and emblem as well as recognize characters and numbers of vehicle license plate using hybrid and seven segment pattern vector. To show the efficiency of the proposed algorithm, we tested it on real vehicle images of implemented vehicle recognition system in highway toll gate and found that the proposed method shows good feature detection/classification performance regardless of irregular environment conditions as well as noise, size, and location of vehicles. And also, the proposed algorithm may be utilized for catching criminal vehicles, unmanned toll collection system, and unmanned checking incoming/outcoming vehicles to an institution.

• Journal of Biosystems Engineering
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• v.36 no.1
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• pp.40-47
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• 2011

Image analysis algorithm for the quality evaluation of ginseng seedling was investigated. The images of ginseng seedling were acquired with a color CCD camera and processed with the image analysis methods, such as binary conversion, labeling, and thinning. The processed images were used to calculate the length and weight of ginseng seedlings. The length and weight of the samples could be predicted with standard errors of 0.343 mm, and 0.0214 g respectively, $R^2$ values of 0.8738 and 0.9835 respectively. For the evaluation of the three quality grades of Gab, Eul, and abnormal ginseng seedlings, features from the processed images were extracted. The features combined with the ratio of the lengths and areas of the ginseng seedlings efficiently differentiate the abnormal shapes from the normal ones of the samples. The grade levels were evaluated with an efficient pattern recognition method of support vector machine analysis. The quality grade of ginseng seedling could be evaluated with an accuracy of 95% and 97% for training and validation, respectively. The result indicates that color image analysis with support vector machine algorithm has good potential to be used for the development of an automatic sorting system for ginseng seedling.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1644-1649
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• 2019

With the rapid development of mobile communication systems, various mobile convergence services are appearing and data traffic is exploding accordingly. Because the number of base stations to support these surging devices is also increasing, from a network provider's point of view, reducing energy consumption through these mobile communication networks is one of the most important issues. Therefore, in this paper, we apply the DBSCAN (density-based spatial clustering of applications with noise) algorithm, one of the representative user-density based clustering algorithms, in order to extract the dense area with user density and apply the thinning process to each extracted sub-network to efficiently control the mode of the base stations. Extensive simulations show that the proposed algorithm has better performance results than the conventional algorithms with respect to area throughput and energy efficiency.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.102-110
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• 1992

In this paper, a new method of character recognition is proposed. It uses density information, in addition to positional and directional information generally used, to recognize a character. Four directional feature primitives are extracted from the thinning templates on the observation that the output of the templates have directional property in general. A simple and fast feature extraction scheme is possible. Features are organized from recursive nonary tree(N-tree) that corresponds to normalized character area. Each node of the N-tree has four directional features that are sum of the features of it's nine sub-nodes. Every feature primitive from the templates are added to the corresponding leaf and then summed to the upper nodes successively. Recognition can be accomplished by using appropriate feature level of N-tree. Also, effectiveness of each node's feature vector was tested by experiment. A method to implement the proposed feature vector organization algorithm into hardware is proposed as well. The third generation node, which is 4$\times$4, is used as a unit processing element to extract features, and it was implemented in hardware. As a result, we could observe that it is possible to extract feature vector for real-time processing.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.411-420
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• 1999

In geology, lineament features have been used to identify geological events, and many of scientists have been developed the algorithm that can be applied with the computer to recognize the lineaments. We choose several edge detection filter, line detection filters and Hough transform to detect an edge, line, and to vectorize the extracted lineament features, respectively. firstly the edge detection filter using a first-order derivative is applied to the original image In this step, rough lineament image is created Secondly, line detection filter is used to refine the previous image for further processing, where the wrong detected lines are, to some extents, excluded by using the variance of the pixel values that is composed of each line Thirdly, the thinning process is carried out to control the thickness of the line. At last, we use the Hough transform to convert the raster image to the vector one. A Landsat image is selected to extract lineament features. The result shows the lineament well regardless of directions. However, the degree of extraction of linear feature depends on the values of parameters and patterns of filters, therefore the development of new filter and the reduction of the number of parameter are required for the further study.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.818-823
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• 2008

In this paper, we propose a feature extraction method which extracts directional features of handwritten numerals by using the projection runlength. Our directional featrures are obtained from four directional images, each of which contains horizontal, vertical, right-diagonal and left-diagonal lines in entire numeral shape respectively. A conventional method which extracts directional features by using Kirsch masks generates edge-shaped double line directional images for four directions, whereas our method uses the projections and their runlengths for four directions to produces single line directional images for four directions. To obtain the directional projections for four directions from a numeral image, some preprocessing steps such as thinning and dilation are required, but the shapes of resultant directional lines are more similar to the numeral lines of input numerals. Four [$4{\times}4$] directional features of a numeral are obtained from four directional line images through a zoning method. By using a hybrid feature which is made by combining our feature with the conventional features of a mesh features, a kirsch directional feature and a concavity feature, higher recognition rates of the handwrittern numerals can be obtained. For recognition test with given features, we use a multi-layer perceptron neural network classifier which is trained with the back propagation algorithm. Through the experiments with the handwritten numeral database of Concordia University, we have achieved a recognition rate of 97.85%.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.11 s.176
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• pp.82-90
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• 2005

Recently, the in-line vision inspection has become the subject of growing research area in the visual control systems and robotic intelligent fields that are required exact three-dimensional pose. The objective of this article is to study the pc based in line visual inspection with the hand-eye structure. This paper suggests three dimensional structured light measuring principle and design method of laser sensor header. The hand-eye laser sensor have been studied for a long time. However, it is very difficult to perform kinematical analysis between laser sensor and robot because the complicated mathematical process are needed for the real environments. In this problem, this paper will propose auto-calibration concept. The detail process of this methodology will be described. A new thinning algorithm and constrained hough transform method is also explained in this paper. Consequently, the developed in-line inspection module demonstrate the successful operation with hole, gap, width or V edge.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.900-907
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• 2000

The three-dimensional turbulent flow in curved pipes susceptible to flow-accelerated corrosion has been analyzed numerically to predict the pressure and shear stress distributions on the inner surface of the pipes. The analysis employs the body-fitted non-orthogonal curvilinear coordinate system and a standard $ {\kappa}-{\varepsilon}$ turbulence model with wall function method. The finite volume method is used to discretize the governing equations. The convection term is approximated by a high-resolution and bounded discretization scheme. The cell-centered, non-staggered grid arrangement is adopted and the resulting checkerboard pressure oscillation is prevented by the application of a modified version of momentum interpolation scheme. The SIMPLE algorithm is employed for the pressure and velocity coupling. The numerical calculations have been performed for two curved pipes with different bend angles and curvature radii, and discussions have been made on the distributions of the primary and secondary flow velocities, pressure and shear stress on the inner surface of the pipe to examine applicability of the present analysis method. As the result it is seen that the method is effective to predict the susceptible systems or their local areas where the fluid velocity or local turbulence is so high that the structural integrity can be threatened by wall thinning degradation due to flow-accelerated corrosion.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.453-459
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• 2015

In this paper, we propose a new digit recognition method based on opened enclosure. In the proposed method, each digit is divided into two parts, an upper part and a lower part, which are based on a cutting line that is modified depending on the number of intersection points. In the simulation, the performance evaluation through the data acquisition and application of the proposed algorithm was carried out and the result was presented.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.3
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• pp.131-137
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• 2006

The secondary system of nuclear power plants consists of sophisticated piping systems operating in very aggressive erosion and corrosion environments, which make a piping system vulnerable to the wear and degradation due to the several chemical components and high flow rate (~10 m/sec) of the coolant. To monitor the wear and degradation on a pipe, the vibration signals are measured from the pipe with an accelerometer For analyzing the vibration signal the time-frequency analysis (TFA) is used, which is known to be effective for the analysis of time-varying or transient signals. To reduce the inteferences (cross-terms) due to the bilinear structure of the time-frequency distribution, an adaptive cone-kernel distribution (ACKD) is proposed. The cone length of ACKD to determine the characteristics of distribution is optimally selected through an adaptive algorithm using the normalized Shannon's entropy And the ACKD's are compared with the results of other analyses based on the Fourier Transform (FT) and other TFA's. The ACKD shows a better signature for the wear/degradation within a pipe and provides the additional information in relation to the time that any analysis based on the conventional FT can not provide.