• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.611-618
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• 2003

In this paper, we describe a fuzzy inference approach for detecting and classifying shot transitions in video sequences. Our approach basically extends FAM (Fuzzy Associative Memory) to detect and classify shot transitions, including cuts, fades and dissolves. We consider a set of feature values that characterize differences between two consecutive frames as input fuzzy sets, and the types of shot transitions as output fuzzy sets. The inference system proposed in this paper is mainly composed of a learning phase and an inferring phase. In the learning phase, the system initializes its basic structure by determining fuzzy membership functions and constructs fuzzy rules. In the inferring phase, the system conducts actual inference using the constructed fuzzy rules. In order to verify the performance of the proposed shot transition detection method experiments have been carried out with a video database that includes news, movies, advertisements, documentaries and music videos.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.2
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• pp.103-111
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• 2014

The wave power, extracted from a circular array of small power buoys, is investigated under the potential theory. It is assumed that the buoy's radius, the draft, and the separation distance are much smaller than the water depth, the wave length, and the radius of a circular deployment area. The boundary value problem involving the macro-scale boundary condition on the mean surface covered by buoys is solved using the eigenfunction expansion method. The capture width, which is defined as the ratio of the extracted power to the wave power per unit length of the incident wave crest, is assessed for various combinations of packing ratio, radius of a circular array, and PTO damping coefficient. It is found that the circular array deployment is more effective in the viewpoint of efficiency than the single large buoy of the same total displaced volume.

• Journal of the Korean GEO-environmental Society
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• v.10 no.6
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• pp.135-141
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• 2009

Fracturing technique using fluid injection into the borehole is widely used technology in the industry for the geothermal heat, oil, and gas extraction. Dealing with fluid-driven natural fractures such as dike and vein indirectly, design technology would be improved by adapting their principles. In this paper, mechanical interaction between the segments is evaluated by modeling highly segmented and closely spaced fluid-driven natural fractures. The number of segments is 71 with 3,339 measured apertures in which the interaction is considerably predicted. To evaluate mechanical interaction, boundary collocation method is used and the net pressure is calculated by using least square method to fit measured apertures. As a result, in case that mechanical interaction is considered, two pressures as fitting parameters are sufficient to capture measured apertures.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.224-229
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• 1999

In the field of speech recognition, the research area can be classified into the following two categories: one which is concerned with the development of phoneme-level recognition system, the other with the efficiency of word-level recognition system. The resonable phoneme-level recognition system should detect the phonemic boundaries appropriately and have the improved recognition abilities all the more. The traditional LPC methods detect the phoneme boundaries using Itakura-Saito method which measures the distance between LPC of the standard phoneme data and that of the target speech frame. The MFCC methods which treat spectral transitions as the phonemic boundaries show the lack of adaptability. In this paper, we present new speech recognition system which uses auto-correlation method in the phonemic boundary detection process and the multi-layered Feed-Forward neural network in the recognition process respectively. The proposed system outperforms the traditional methods in the sense of adaptability and another advantage of the proposed system is that feature-extraction part is independent of the recognition process. The results show that frame-unit phonemic recognition system should be possibly implemented.

• Korean Journal of Remote Sensing
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• v.19 no.2
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• pp.159-169
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• 2003

This paper presents a method for automatic 3-d building reconstruction using high resolution aerial imagery. First, by using edge preserving filtering, noise is eliminated and then images are segmented by watershed algorithm, which preserves location of edge pixels. To extract line segments between control points from boundary of each region, we calculate curvature of each pixel on the boundary and then find the control points. Line segment linking is performed according to direction and length of line segments and the location of line segments is adjusted using gradient magnitudes of all pixels of the line segment. Coplanar grouping and pplygonal patch formation are performed per region by selecting 3-d line segments that are matched using epipolar geometry and flight information. The algorithm has been applied to high resolution aerial images and the results show accurate 3D building reconstruction.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.211-217
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• 2006

Growing urban areas modify patterns of local land use and land cover. Land use changes associated with urban expansion. One way to understand and document land use change and urbanization is to establish benchmark maps compiled from satellite imagery. Old satellite Imagery is useful data to extract urban information. CORONA is a photo satellite reconnaissance program used from 1960 to 1972 and its imagery was declassified and has been available to the public since 1995. Since CORONA images are collected with panoramic cameras, several types of geometric distortions are involved. In this study we proposed mathematical modeling method which use modified collinearity equations. After the geometric modeling, we mosaicked images. We can successfully extract urban boundaries using GLCM method and visual interpretation in CORONA (1972) and SPOT (1995) imagery and detect urban changes in Seoul quantitatively.

• The Korean Journal of Nuclear Medicine
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• v.32 no.5
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• pp.414-424
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• 1998

Purpose: Cross-modality coregistration of positron emission tomography (PET) and magnetic resonance imaging (MR) could enhance the clinical information. In this study we propose a refined technique to improve the robustness of registration, and to implement more realistic visualization of the coregistered images. Materials and Methods: Using the sinogram of PET emission scan, we extracted the robust head boundary and used boundary-enhanced PET to coregister PET with MR. The pixels having 10% of maximum pixel value were considered as the boundary of sinogram. Boundary pixel values were exchanged with maximum value of sinogram. One hundred eighty boundary points were extracted at intervals of about 2 degree using simple threshold method from each slice of MR images. Best affined transformation between the two point sets was performed using least square fitting which should minimize the sum of Euclidean distance between the point sets. We reduced calculation time using pre-defined distance map. Finally we developed an automatic coregistration program using this boundary detection and surface matching technique. We designed a new weighted normalization technique to display the coregistered PET and MR images simultaneously. Results: Using our newly developed method, robust extraction of head boundary was possible and spatial registration was successfully performed. Mean displacement error was less than 2.0 mm. In visualization of coregistered images using weighted normalization method, structures shown in MR image could be realistically represented. Conclusion: Our refined technique could practically enhance the performance of automated three dimensional coregistration.

• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.915-924
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• 2002

Conventional Systems for parcel sorting consist of two sequences as loading the parcel into conveyor belt system and post-code input. Using bar code information, the parcels to be recorded and managed are recognized. This paper describes a 32 $\times$ 32 sized mini-block inspection to extract bar code Region of Interest (ROI) from the line Charged Coupled Device (CCD) camera capturing image of moving parcel at 2m/sec speed. Firstly, the Min-Max distribution of the mini-block has been applied to discard the background of parcel and region of conveying belts from the image. Secondly, the diagonal inspection has been used for the extraction of letters and bar code region. Five horizontal line scanning detects the number of edges and sizes and ROI has been acquired from the detection. The wrong detected area has been deleted by the comparison of group size from labeling processes. To correct excluded bar code region in mini-block processes and for analysis of bar code information, the extracted ROI 8 boundary points and decline distribution have been used with central axis line adjustment. The ROI extraction and central axis creation have become enable within 60～80msec, and the accuracy has been accomplished over 99.44 percentage.

• Proceedings of the Korean Vacuum Society Conference
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• 2000.02a
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• pp.186-186
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• 2000

After LeComber et al. reported the first amorphous hydrogenated silicon (a-Si: H) TFT, many laboratories started the development of an active matrix LCDs using a-Si:H TFTs formed on glass substrate. With increasing the display area and pixel density of TFT-LCD, however, high mobility TFTs are required for pixel driver of TF-LCD in order to shorten the charging time of the pixel electrodes. The most important of these drawbacks is a-Si's electron mobiliy, which is the speed at which electrons can move through each transistor. The problem of low carier mobility for the a-Si:H TFTs can be overcome by introducing polycrystalline silicon (poly-Si) thin film instead of a-Si:H as a semiconductor layer of TFTs. Therefore, poly-Si has gained increasing interest and has been investigated by many researchers. Recnetly, fabrication of such poly-Si TFT-LCD panels with VGA pixel size and monolithic drivers has been reported, . Especially, fabricating poly-Si TFTs at a temperature mach lower than the strain point of glass is needed in order to have high mobility TFTs on large-size glass substrate, and the monolithic drivers will reduce the cost of TFT-LCDs. The conventional methods to fabricate poly-Si films are low pressure chemical vapor deposition (LPCVD0 as well as solid phase crystallization (SPC), pulsed rapid thermal annealing(PRTA), and eximer laser annealing (ELA). However, these methods have some disadvantages such as high deposition temperature over $600^{\circ}C$, small grain size (<50nm), poor crystallinity, and high grain boundary states. Therefore the low temperature and large area processes using a cheap glass substrate are impossible because of high temperature process. In this study, therefore, we have deposited poly-Si thin films on si(100) and glass substrates at growth temperature of below 40$0^{\circ}C$ using newly developed high rate magnetron sputtering method. To improve the sputtering yield and the growth rate, a high power (10~30 W/cm2) sputtering source with unbalanced magnetron and Si ion extraction grid was designed and constructed based on the results of computer simulation. The maximum deposition rate could be reached to be 0.35$\mu$m/min due to a high ion bombardment. This is 5 times higher than that of conventional sputtering method, and the sputtering yield was also increased up to 80%. The best film was obtained on Si(100) using Si ion extraction grid under 9.0$\times$10-3Torr of working pressure and 11 W/cm2 of the target power density. The electron mobility of the poly-si film grown on Si(100) at 40$0^{\circ}C$ with ion extraction grid shows 96 cm2/V sec. During sputtering, moreover, the characteristics of si source were also analyzed with in situ Langmuir probe method and optical emission spectroscopy.

• Korean Journal of Remote Sensing
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• v.20 no.4
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• pp.261-274
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• 2004

The feature extraction using remotely sensed imagery has been recognized one of the important tasks in remote sensing applications. As the high-resolution imagery are widely used to the engineering purposes, need of more accurate feature information also is increasing. Especially, in case of the automatic extraction of linear feature such as road using mid or low-resolution imagery, several techniques was developed and applied in the mean time. But quantitatively comparative analysis of techniques and case studies for high-resolution imagery is rare. In this study, we implemented a computer program to perform and compare GDPA (Gradient Direction Profile Analysis) algorithm and Hough transformation. Also the results of applying two techniques to some images were compared with road centerline layers and boundary layers of digital map and presented. For quantitative comparison, the ranking method using commission error and omission error was used. As results, Hough transform had high accuracy over 20% on the average. As for execution speed, GDPA shows main advantage over Hough transform. But the accuracy was not remarkable difference between GDPA and Hough transform, when the noise removal was app]ied to the result of GDPA. In conclusion, it is expected that GDPA have more advantage than Hough transform in the application side.