• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.142-148
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• 2004

In this paper, we propose the color fuzzy decision algorithm to face segmentation in a color image. Our algorithm can segment without the user's interaction by fuzzy decision marking. And it removes small parts such as a noise using wavelet morphology in the image obtained by applying the fuzzy decision algorithm. Also, it merges and chooses the face region in each quantization image through rough sets. This video object division algorithm is shown to be superior to a conventional algorithm.

• Aerospace Engineering and Technology
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• v.6 no.1
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• pp.213-221
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• 2007

This paper showed how to analysis the object-based classification for wildfire fuel type map using Hyperion hyperspectral remote sensing data acquired in April, 2002 and compared the results of the object-based classification with the results of the pixel-based classification. Our methodological approach for wildfire fuel type map firstly processed correcting abnormal pixels and atypical bands and also calibrating atmospheric noise for enhanced image quality. Fuel type map is characterized by the results of the spectral mixture analysis(SMA). Object-based approach was based on segment-based endmember selection, while pixel-based method used standard SMA. To validate and compare, we used true-color high resolution orthoimagery.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.560-574
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• 2010

Recently, many people can easily contact video telephony service through the mobile terminal owing to the commercialization of 3G communication technology. However, the quality of the serviced video telephony has been not good yet by the actual mobile restrictions. For solving quality problems, this paper presents the design of the object-based video CODEC using hybrid transform in mobile video telephony. The proposed design firstly segment each frame into a significant object and an insignificant object. The proposed design is to improve the quality of a significant object by limiting the bit rate of a insignificant object. Thus, we compress a significant object with high quality and low compression ratio and compress an insignificant object with low quality and high compression ratio. Furthermore, we control the bit rate of the video stream in the limited bandwidth by adjusting the compression ratio of each object. From experimental results, we confirmed that our method has more higher quality than methods in the conventional CODECs at the significant region on the same bit rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.1
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• pp.80-89
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• 1992

This paper presents algorithms which are region labeling and data structure of a boundary segmentation as image intermediate description process. In the method, the algorithms are region labeling, boundary segmentation, line and curve fitting and extracting data structure of each segment. As a result, a data structure of image is described by a set of region number, segment number, line or curve, starting point and end point of each segment and coefficient of line or curve. These data structures would serve for higher level processing as object recognition. For example we will use this data structure to solve the correspondence problem of stereoscopic image information. And we verified these algorithms through the image reconstruction of data structure.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1126-1134
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• 2017

A variety of medical service applications in the field of the Internet of Things (IoT) are being studied. Segmentation is important to identify meaningful regions in images and is also required in 3D images. Previous methods have been based on gray value and shape. The Visible Korean dataset consists of serially sectioned high-resolution color images. Unlike computed tomography or magnetic resonance images, automatic segmentation of color images is difficult because detecting an object's boundaries in colored images is very difficult compared to grayscale images. Therefore, skilled anatomists usually segment color images manually or semi-automatically. We present an out-of-core 3D segmentation method for large-scale image datasets. Our method can segment significant regions in the coronal and sagittal planes, as well as the axial plane, to produce a 3D image. Our system verifies the result interactively with a multi-planar reconstruction view and a 3D view. Our system can be used to train unskilled anatomists and medical students. It is also possible for a skilled anatomist to segment an image remotely since it is difficult to transfer such large amounts of data.

• Journal of Multimedia Information System
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• v.9 no.3
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• pp.233-244
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• 2022

A MATLAB program was developed to calculate the half-wavelength of a sine-curve baseband signal with white noise by using an autocorrelation function, a SG filter, and zero-crossing detection. The frequency of the input signal can be estimated from 1) the first zero-crossing (corresponding to ¼λ) and 2) the R value (the Y axis of the correlogram) at the center of the segment. Thereby, the frequency information of the preceding segment can be obtained. If the segment size were optimized, and a portion with a large zero-crossing dynamic range were obtained, the frequency discrimination ability would improve. Furthermore, if the values of the correlogram for each frequency prepared on the CPU side were prepared in a table, the volume of calculations can be reduced by 98%. As background, period detection by autocorrelation coefficients requires an integer multiple of 1/2λ (when using a sine wave as the object of the autocorrelation function), otherwise the correlogram drawn by R value will not exhibit orthogonality. Therefore, it has not been used in bio-telemetry where the frequencies move around.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.3
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• pp.79-87
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• 1996

A new method for recognizing and locating partially occluded or overlapped two-dimensional objects regardless of their size, translation, and rotation, is presented. Dominant points approximating occuluding contoures of objects are generated by finding local maxima of smoothed k-cosine function, and then used to guide the contour segment matching procedure. Primitives between the dominant points are produced by projecting the local contours onto the line between the dominant points. Robust classification of primitives. Which is crucial for reliable partial shape matching, is performed using adaptive resonance theory (ART2). The matched primitives having similar scale factors and rotation angles are detected in the hough space to identify the presence of the given model in the object scene. Finally the translation vector is estimated by minimizing the mean squred error of the matched contur segment pairs. This model-based matching algorithm may be used in diveerse factory automation applications since models can be added or changed simply by training ART2 adaptively without modifying the matching algorithm.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.505-508
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• 2003

The current paper proposes a new vertex selection scheme for polygon-based contour ceding. To efficiently characterize the shape of an object, we incorporate the curvature information in addition to the conventional maximum distance criterion in vertex selection process. The proposed method consists of “two-step procedure.” At first, contour pixels of high curvature value are selected as key vertices based on the curvature scale space (CSS), thereby dividing an overall contour into several contour-segments. Each segment is considered as an open contour whose end points are two consecutive key vertices and is processed independently. In the second step, vertices for each contour segment are selected using progressive vertex selection (PVS) method in order to obtain minimum number of vertices under the given maximum distance criterion ( $D_{MAX}$). Experimental results are presented to compare the approximation performances of the proposed and conventional methods.s.

• 한국공간정보시스템학회:학술대회논문집
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• 2003.11a
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• pp.159-162
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• 2003

In this paper, to find probable collision positions between moving object and terrain in 3D space efficiently, we use a model, similar to Ray Tracing, which finds the triangles intersected by a directed line segment from a large amount of triangles. We try to reduce dead space as much as possible to find candidate triangles intersected by a directed line segment than previous work's. A new modified octree, LBV-Octree(Least Bounding Voxel Octree), is proposed, and we have a ray tracing with it. In the experiment, ray tracing with LBV-Octree provides $5%{\sim}11%$ better performance than with classical octree.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.228-233
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• 1997

An efficient corner matching algorithm is developed to minimize the amount of calculation. To reduce the amount of calculation, all available information from a corner detector is used to make model. This information has uncertainties due to discretization noise and geometric distortion, and this is represented by fuzzy rule base which can represent and handle the uncertainties. Form fuzzy inference procedure, a matched segment list is extracted, and resulted segment list is used to calculate the transformation between object of model and scene. To reduce the false hypotheses, a vote and re-vote method is developed. Also an auto tuning scheme of the fuzzy rule base is developed to find out the uncertainties of features from recognized results automatically. To show the effectiveness of the developed algorithm, experiments are conducted for images of real electronic components.