• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.116-118
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• 1997

In hippocampal morphology Abnormalities, including unilateral or bilateral volume loss, are known to occur in epilepsy, Alzheimer's disease, and in certain amnestic syndromes. To detect such abnormalities in hippocampal morphology, we present a method that combines region growing and dynamic contour model to detect hippocampus from MRI brain data. The segmentation process is performed two steps. First region growing with a seed point is performed in the region of hippocampus and the initial contour of dynamic contour model is obtained. Second, the initial contour is modified on the basis of criteria that integrate energy with contour smoothness and the image gradient along the contour. As a result, this method improves fairly sensitivity to the choice of the initial seed point, which is often seen by conventional contour model. The power and practicality of this method have been tested on two brain datasets. Thus, we have developed an effective algorithm to extract hippocampus from MRI brain data.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.8
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• pp.11-16
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• 2008

In this paper, firstly we made of the rapid thermal processor equipment with the specifically useful structure to measure wafer stress. Secondly we made of the laser interferometry to inspect the wafer surface curvature based on the large deformation theory. And then the wafer surface fringe image was obtained by experiment, and the full field stress distribution of wafer surface comes into view by signal processing with thining and pitch mapping. After wafer was ground by 1mm and polished from the back side to get easily deformation, and it was heated by three to four times thermal treatments at about 1000 degree temperature. Finally the severe deformation between wafer before and after the heat treatment was shown.

• Publications of The Korean Astronomical Society
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• v.15 no.spc1
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• pp.1-13
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• 2000

We review the early historical developement of astronomical spectrographs, properties of emission line spectra of HII regions in spiral galaxies, and absorption line features of galactic globular clusters. Emission line spectra of HII regions within three spiral galaxies NGC 300, NGC 1365, and NGC 7793, which were observed from AAT/IPCS, had been analysed, and we discuss the abundances of elements in HII regions and the radial abundace gradients through the galaxies. The radial UBV color variations of two globular clusters, NGC 1851 and NGC 2808, were examined for correlations with radial variations of several absorption lines in the integrated spectra, which were obtained from SAAO 74 inch telescope and image tube spectrograph. Nine giant star's spectra in NGC 3201 were also obtained and analysed for the radial abundance gradients in the globular cluster. The results show that the presence of a radial color gradient in a globular cluster is correlated with the presence of abundance gradients. Finally, we suggest some scientific programs for the new high dispersion spectrograph, which will be installed to the BOAO 1.8m telescope.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.142-149
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• 2016

This paper proposes a method to detect LP(License Plate) of vehicles in indoor and outdoor parking lots. In restricted environment, there are many conventional methods for detecting LP. But, it is difficult to detect LP in natural and complex scenes with background clutters because several patterns similar with text or LP always exist in complicated backgrounds. To verify the performance of LP text detection in natural images, we apply MB-LGP feature by combining with ensemble machine learning algorithm in purpose of selecting optimal features of small number in huge pool. The feature selection is performed by adaptive boosting algorithm that shows great performance in minimum false positive detection ratio and in computing time when combined with cascade approach. MSER is used to provide initial text regions of vehicle LP. Throughout the experiment using real images, the proposed method functions robustly extracting LP in natural scene as well as the controlled environment.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.12
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• pp.1232-1239
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• 2009

This paper proposes an exploration strategy to efficiently find a specific place in large unknown environments with wall-following based path planning. Many exploration methods proposed so far showed good performance but they focused only on efficient planning for modeling unknown environments. Therefore, to successfully accomplish the room finding task, two additional requirements should be considered. First, suitable path-planning is needed to recognize the room number. Most conventional exploration schemes used the gradient method to extract the optimal path. In these schemes, the paths are extracted in the middle of the free space which is usually far from the wall. If the robot follows such a path, it is not likely to recognize the room number written on the wall because room numbers are usually too small to be recognized by camera image from a distance. Second, the behavior which re-explores the explored area is needed. Even though the robot completes exploration, it is possible that some rooms are not registered in the constructed map for some reasons such as poor recognition performance, occlusion by a human and so on. With this scheme, the robot does not have to visit and model the whole environment. This proposed method is very simple but it guarantees that the robot can find a specific room in most cases. The proposed exploration strategy was verified by various experiments.

• Journal of Broadcast Engineering
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• v.20 no.3
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• pp.440-448
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• 2015

A pedestrian collision warning system which makes a judgement of pedestrian's intention to help avoiding hitting accidents is proposed. This system uses the image sequences obtained from a car black box as well as vehicle's speed obtained from a GPS. It detects pedestrians, if any, based on the Histogram of Gradient method and extracts several information such as the pedestrian's relative positions, the direction of motion vectors, and distance between vehicle and pedestrian . A fuzzy logic based on these extracted information is applied to analyze the pedestrian's safety levels. When the safety level is determined to be danger, an alarm is triggered to the driver. The performance of the proposed algorithm is tested under various driving scenarios, which shows it works successfully in real-time.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.10
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• pp.3038-3047
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• 1996

In telerobot systems, visual servoing of a task object for a slave arm with an eye-in-hand has drawn an interesting attention. As such a task ingenerally conducted in an unstructured environment, it is very difficult to define the inverse feature Jacobian matrix. To overcome this difficulty, this paper proposes an auto-tuning fuzzy rule-based visual servo algorithm. In this algorithm, a visual servo controller composed of fuzzy rules, receives feature errors as inputs and generates the change of have position as outputs. The fuzzy rules are tuned by using steepest gradient method of the cost function, which is defined as a quadratic function of feature errors. Since the fuzzy rules are tuned automatically, this method can be applied to the visual servoing of a slave arm in real time. The effctiveness of the proposed algorithm is verified through a series of simulations and experiments. The results show that through the learning procedure, the slave arm and track object in real time with reasonable accuracy.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.5 s.176
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• pp.1254-1260
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• 2000

There have been many developments in super precision working technique and working method up to, now. But, it is very difficult to evaluate working surface accurately without the technicians experience and judgment. Surface roughness tester using stylus was used to measure surface condition generally But this method is not so desirable because of damage on test piece caused by contact between the workpiece and the stylus sensor. As a result, non-contact method was known as a good way to carry, out this process without damage. However, this is a difficult one among the various measuring methods. So we are tying to suggest a new method using texture analysis through image processing to get a surface information in worked test piece. Co-occurrence matrix using difference of gray levels between a pixel and its neighboring one was used to study behavior of surface roughness and to J acquire data for analysis. Standard specimen was adapted to verify this research. We suggest texture information method in order to evaluate surface state for the best measurement system.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.356-358
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• 2002

MRI, particularly diffusion weighted imaging (DWI), plays vital roles in detection of the acute brain infarction$\^$1-4/ and others metabolic changes of biological tissues. In general, every molecule in biological tissues may diffuse and move randomly in three-dimensional space. However, in clinical diagnosis, only 2D-DWI is used. The authors have developed a new method for rapid three-dimensional DWI (3D-DWI). In this method, by refocusing of the magnetized spin with the applied gradient field, direction of which is opposite to phase encoding field. Magnetized spin of $^1$H is kept under the SSFP (steady state free precession)$\^$5-6/. Under SSFP, in addition of FID, spin echo and stimulated echo are also generated, so the acquired signal is increased. The signal intensity is increased depending on flip angle (FA) of magnetized spin. This phenomenon is confirmed by human brain and phantom studies. The performance of this method is quantitatively analyzed by using both of conventional spin echo DWI and 3D-DWI. From experimental results, three dimensional diffusion weighted images are obtained correctly for liquid phantoms (water, acetone and oil), diffusion coefficient is enhanced in each image. Therefore, this method will provide useful information for clinical diagnosis.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.1
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• pp.89-96
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• 2001

In this paper, a noise-tolerant generalized symmetry transform(NTGST) is proposed and implemented as a context-free attention operator for efficient detection of multi-object. In contrast to the conventional context-free attention operator based on the GST in which only the magnitude and the symmetry of the pixel pairs are taken into account, the proposed NTGST additionally takes into account the convergence and the divergence of the radial orientation of the intensity gradient of the pixel pair. Thus, the proposed attention operator can easily detect multiple objects out of the noisy and complex backgrounded image. Experiments are conducted on various synthetic and real images, and the proposed NTGST is proved to be effective in multi-object detection from the noisy and complex backgrounds.