• Investigative Magnetic Resonance Imaging
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• v.4 no.2
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• pp.100-106
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• 2000

Purpose : To evaluate the usefulness of cerebral blood flow measurement applied to perfusion weighted image with short-scan time single shot gradient echo-planar technique in measuring cerebral blood volume(rCBV) of normal rabbits. Materials and methods : With 2.1-3.6 kg weighted rabbits, image is acquired when they are in supine position in children positioner. Perfusion weighted image is acquired to 44 seconds per 1 second successively. After 4 seconds later, Gd-DTPA 2ml are injected into int. jugular vein with 2 ml per second and normal saline is also injected after that. Same technique is applied 2 times per 30 minites in same rabbit. After Image is obtained in two part of cerebral cortex at vertex, convexity, in one of basal ganglia with choosing about $3-5{\textrm{mm}^2}$ areas. Curve of signal intensity changes in time sequence is drawn. After this images are transmitted by PC and software IDL, regional cerebral blood volume is measured with imaging processing program made by us. Results : With 22 of 24 rabbits, satisfactory 1-2 signal intensity versus time curve is made. Cerebral blood capacity and contrast media stay time (ST) is measured in two cerebral cortex and basal ganglia refering in parietal cerebral cortex. Mean focal cerebral blood flow capacity ratio in cortex was $0.97{\pm}0.35$ and in basal ganglia, $0.99{\pm}0.37$, mean contrast media stay time in cortex was $9.83{\pm}1.63$ sec and in basal gaiglia, $9.42{\pm}1.14$ sec, but there was no statistically significant difference between two areas ($\rho$=0.05). Conclusion : In cerebral cortex and basal ganglia, there is no difference in mean focal blood volume and mean contrast stay time. Therefore, PWI is useful in cerebral blood flow and early diagnosis, prognosis of cerebral ischemic disease. Hereafter, it is helpful in analysing cerebral blood flow changes with comparison difference in rCBV between normal tissue and ischemic tissue, and that with DWI finding in infarcted patient.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1150-1158
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• 2010

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problem. First, in preprocessing part, we use a CCD camera to obtain a picture frame in real-time. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. We use an AdaBoost algorithm proposed by Viola and Jones, which is exploited for the detection of facial image area between face and non-facial image area. As the feature extraction algorithm, PCA method is used. In this study, the PCA method, which is a feature extraction algorithm, is used to carry out the dimension reduction of facial image area formed by high-dimensional information. Secondly, we use pRBFNNs to identify the ID by recognizing unique pattern of each person. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. Coefficients of connection weight identified with back-propagation using gradient descent method. The output of pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of the Particle Swarm Optimization. The proposed pRBFNNs are applied to real-time face recognition system and then demonstrated from the viewpoint of output performance and recognition rate.

• Journal of the Korean Society of Combustion
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• v.21 no.4
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• pp.30-38
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• 2016

Flame structure of co-firing coal and palm kernel shell (PKS) was investigated in a pulverized coal swirl burner by particle image velocimetry (PIV). The pulverized coal swirl flame is operated with a PKS blending ratio of 10%, 20%, and 30%. For all operating conditions, flame structures such as internal recirculation zone (IRZ), outer recirculation zone (ORZ), and exhaust tube vortex (ETV) were observed. In the center of flame, the strong velocity gradient is occurred at the stagnation point where the volatile gas combustion actively takes place and the acceleration is increased with higher PKS blending ratio. OH radical shows the burned gas region at the stagnation point and shear layer between IRZ and ORZ. In addition, OH radical intensity increases for a co-firing condition because of high volatile matter from PKS. Because the volatile gas combustion takes place at lower temperature, co-firing condition (more than 20%) leads to oxygen deficiency and reduces the combustibility of coal particle near the burner. Therefore, increasing PKS blending ratio leads to higher OH radical intensity and lower temperature.

• The Transactions of the Korea Information Processing Society
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• v.3 no.4
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• pp.866-876
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• 1996

A feature extraction method for the objects that have a circular cross section is proposed.To implement a robust recognition system which can effectively deal with various types of 2-dimensional image and 3-dimensional image, both 2- dimensional information and 3-dimensional information should be collectively extracted and combined for the optimum. For this, this paper presents a feature extraction method for 3-dimensional objects, particularly for the objects with a circular cross section which most objects in the real world are known to have. Firstly, the Z gradient is proposed to extract the shape information from those objects. Using this information, normal vectors are derived from the surface patches. The intersection points between the vectors are applied to the geometric feature extraction.Also, for more accurate recognition, a feature extraction method for between surface regions is proposed.Finally, the extraction method of function information is investigated for the final recognition process.The usefulness of the proposed method is proved through the experimentation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.3
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• pp.405-417
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• 2001

In this paper, since we currently using surveillance system of analog type bring about waste of resource and efficiency deterioration problems, we describe new solution that design and implementation to the digital surveillance system of new type applying compression techniques and encoding techniques of image data using MPEG-2 international standard. Also, we proposed fast motion estimation algorithm requires much less than the convectional digital surveillance camera system. In this paper a fast motion estimation algorithm is proposed the MPEG-2 video encoding. This algorithm is based on a hybrid use of the block matching technique and gradient technique. Also, we describe a method of moving object extraction directly using MPEG-2 video data. Since proposed method is very simple and requires much less computational power than the conventional object detection methods. In this paper we don't use specific H/W and this system is possible only software encoding, decoding and transmission real-time for image data.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.57-67
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• 1998

In order to extract the contour of interesting object in the image, Kass suggested the Active Contour Model called "Snakes" The speed of this model is slow and this model is sensitive of initialization. In order to improve these problems, Gunn extracted the accurate contour by using two initializations, and operated to less sensitive of initialization. This method could extract more accurate contour than the existing method, but it had no effect in the speed and it was sensitive of noise. This paper applied to the Energy Minimization Algorithm about only the pixel within the window applying the window of $8{\times}8$ size at each contour point consisting Snakes in order to solve these problems. In order to less sensitive of noise which exists within image, it suggests a method that moves the window to vertical direction for the gradient of each contour point.our point.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.41 no.1
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• pp.37-46
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• 2017

Thermal Marangoni flow has been observed inside droplets on heated surfaces, finally resulting in a coffee stain effect. This study aims to visualize and control the thermal Marangoni flow by employing periodic vertical vibration. The variations in the contact angle and internal volume of the droplet as it evaporates is observed by using a combination of continuous light and a still camera. With regard to the internal velocity, the particle image velocimetry system is applied to visualize the internal thermal Marangoni flow. In order to estimate the internal temperature gradient and surface tension on the surface of a droplet, the theoretical model based on the conduction and convection theory of heat transfer is applied. Thus, the internal velocity increases with an increase in plate temperature. The flow directions of the Marangoni and gravitational flows are opposite, and hence, it may be possible to control the coffee stain effect.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.12
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• pp.1165-1172
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• 2009

The laminar boundary layer along a streamwise corner formed by two flat plates intersecting at right angle is measured by using Particle Image Velocimetry(PIV) technique. The free stream velocity ranges from 2.96m/s to 3.0m/s. The angle of incidence of the corner is set to 1.2 degree providing slightly favourable pressure gradient to ensure a laminar flow in the corner region. A round shape leading edge is used and the length of the model is about 1000mm. In the bisector plane, the measurement data show separation type velocity profiles having an inflection point which is a typical characteristic of laminar corner boundary layers. As the distance away from the bisector plane increases, velocity profiles are found to change into the Blasius profile. The change completes around half length of the boundary layer thickness in the bisector plane away from the bisector plane along the plate. In the bisector plane, the growth characteristic of the boundary layer thickness and the approximate similarity of velocity profiles are confirmed from the measurement data.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.139-145
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• 2006

Feature extraction technique in digital images has many applications such as robot vision, medical diagnostic system, and motion video transmission, etc. There are several methods for extracting features in digital images for example nonlinear gradient, nonlinear laplacian, and entropy convolutional filter. However, conventional convolutional filters are usually not efficient to extract features in an image because image feature formation in eyes is more sensitive to dark regions than to bright regions. A few nonlinear filters using difference between arithmetic mean and harmonic mean in a window for extracting sketch features are described in this paper They have some advantages, for example simple computation, dependence on local intensities and less sensitive to small intensity changes in very dark regions. Experimental results demonstrate more successful features extraction than other conventional filters over a wide variety of intensity variations.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.21-30
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• 2005

In this paper, we propose lane detection and trackinB algerian using B-Snake as robust algorithm. One of chief virtues of Lane detection algorithm using B-Snake is that it is possible to specify a wider range of lane structure because B-Spline conform an arbitrary shape by control point set and that it doesn't use any camera parameter. Using a robust algorithm called CHVEP, we find the vanishing point, width of lane and mid-line of lane because of the perspective parallel line and then we can detect the both side of lane mark using B-snake. To demonstrate that this algorithm is robust against noise, shadow and illumination variations in road image, we tested this algorithm about various image divided by weather-fine, rainy and cloudy day. The percentage of correct lane detection is over 95$\%$.