• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.639-647
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• 2018

This paper presents TerraSAR-X and KOMPSAT-5 sigma nought variation according to season and antenna observation configuration in Mongolia. Two types of landcover including bare surface and cropland were examined. The seasonal variation of sigma nought in cropland was about 7 dB and particularly a significant sigma nought reduction occurred after harvest. On the contrary, the Mongolia bare surface provides a consistent sigma nought values for several years with an annual variation less than 2.5 dB of standard deviation. However, the bare soil was relatively sensitive to look-direction (or ascending or descending mode) as well as incidence angle while the cropland was almost independent of antenna look-direction and small incidence angle changes. Although the look-directional variation of bare surface sigma nought was observed in this study, the look-direction anisotropic nature of the surface was not well examined. A further study would be required to account for this feature with various SAR observation configurations.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.49-57
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• 2000

In this study, a new algorithm for canceling a MRI artifact due to the translational motion In the image plane is described. Unlike the conventional iterative phase retrieval algorithm, in which there is no guarantee for the convergence, a direct method for estimating the motion is presented. In previous approaches, the motions in the x(read out) direction and the y(phase encoding) direction were estimated simultaneously. However, the feature of x and y directional motions are different from each other. By analyzing their features, each x and y directional motion is canceled by the different algorithms in two steps. First, it is noticed that the x directional motion corresponds to a shift of the x directional spectrum of the MRI signal, and the non-zero area of the spectrum just corresponds to the projected area of the density function on the x axis. So the motion is estimated by tracing the edges between non-zero area and zero area of the spectrum, and the x directional motion is canceled by shifting the spectrum in an reverse direction. Next, the y directional motion is canceled by using a new constraint condition, with which the motion component and the true image component can be separated. This algorithm is shown to be effective by using a phantom image with simulated motion.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.57-64
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• 2018

In this paper, we propose the automatic detection method for individual region separation using panorama image. Finding areas that contain individual teeth is one of the most important tasks in automating 3D models through individual tooth separation. In the conventional method, the maxillary and mandibular teeth regions are separated using a straight line or a specific CT slide, and the tooth regions are separated using a straight line in the vertical direction. In the conventional method, since the teeth are arranged in a curved shape, there is a problem that each tooth region is incorrectly detected in order to generate an accurate tooth region. This is a major obstacle to automating the creation of individual tooth models. In this study, we propose a method to find the correct tooth curve by using the jawbone curve which is very similar to the tooth curve in order to overcome the problem of finding the area containing the existing tooth. We have proposed a new method to accurately set individual tooth regions using the feature that individual teeth are arranged in a direction similar to the normal direction of the tooth alignment curve. In the proposed method, the maxillary and mandibular teeth can be more precisely separated than the conventional method, and the area including the individual teeth can be accurately set. Experiments using real dental CT images demonstrate the superiority of the proposed method.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.8
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• pp.1254-1264
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• 2002

The purpose of this study was to suggest a direction for golfwear design targeting young female golfers, based on the analysis of their preference of recent sportswear trend. Total 197 respondents, female golfers, were sampled for data gathering, who were asked to answer to the self-report questionnaire with the stimuli of five trendy golfwear styles [i.e., representing recent sportswear trend]. In summary, the results of this study were as follows: 1) The female golfers showed significant difference in their preference of recent sportswear-trend sues, according to their age or marital status. 2) Among the five trendy styles, each of which corresponded to five themes in 2002 S/S sportswear trend, the style of "Retro Chic", a type of retrospective trend theme, was most favored. 3) The female golfers in their twenties residing in Kangnam, were found to have ① relatively higher fashion leadership, and ② higher preference of maximal and kitsch trends, when compared with the rest of the respondents. 4) The most influential design elements in each trendy style, dominating the golfers' preference, varied with the feature of trend themes. 5) Based on the analysis of the young female golfers′ preferences of recent sportswear trend, a direction for golfwear design were suggested.

• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1676-1687
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• 2008

In this paper, we proposed a new multi-view human recognition method based on face and gait features detection algorithm. For getting the position of moving object, we used the different of two consecutive frames. And then, base on the extracted object, the first important characteristic, walking direction, will be determined by using the contour of head and shoulder region. If this individual appears in camera with frontal direction, we will use the face features for recognition. The face detection technique is based on the combination of skin color and Haar-like feature whereas eigen-images and PCA are used in the recognition stage. In the other case, if the walking direction is frontal view, gait features will be used. To evaluate the effect of this proposed and compare with another method, we also present some simulation results which are performed in indoor and outdoor environment. Experimental result shows that the proposed algorithm has better recognition efficiency than the conventional sing]e view recognition method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.6000-6017
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• 2018

This paper presents a new descriptor, named Histograms of Prominent Edge Directions (HPED), for the recognition of facial expressions in a person-independent environment. In this paper, we raise the issue of sampling error in generating the code-histogram from spatial regions of the face image, as observed in the existing descriptors. HPED describes facial appearance changes based on the statistical distribution of the top two prominent edge directions (i.e., primary and secondary direction) captured over small spatial regions of the face. Compared to existing descriptors, HPED uses a smaller number of code-bins to describe the spatial regions, which helps avoid sampling error despite having fewer samples while preserving the valuable spatial information. In contrast to the existing Histogram of Oriented Gradients (HOG) that uses the histogram of the primary edge direction (i.e., gradient orientation) only, we additionally consider the histogram of the secondary edge direction, which provides more meaningful shape information related to the local texture. Experiments on popular facial expression datasets demonstrate the superior performance of the proposed HPED against existing descriptors in a person-independent environment.

• Journal of Sasang Constitutional Medicine
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• v.24 no.4
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• pp.17-27
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• 2012

Objectives : This study proposes developing Sasang Medical Diagnosis Program using Facial form for increase in Sasang Constitution Diagnosis objectivity and putting the Diagnosis Program into practical use. The author presents a review of extant research on Sasang constitution diagnosis utilizing facial feature analysis and suggests an agenda for further research. Methods : For this thesis, a collection of dissertations on the subject of 'Usage of facial form for constitution diagnosis' published until September of 2012 such as RISS4U, OASIS, KISTI, Korean TK were reviewed. The final 33 dissertations were classified into two categories, basic or clinical research and then analyzed. Results : 9 out of 33 dissertations were of basic research and 24 were of clinical research. 1) As result of review of references, a uniform tendency was found in facial form according to Sasang Constitution. 2) In the grade of practical use, facial element is repeatedly used and the facial element of important use has constitutional differences. 3) Standard faces per Sasang Constitution were derived as result of 2-dimensional research. 4) 3-dimensional research focused on improvement of accuracy and reliability of 3D-AFRA, and there has been an attempt to develop a prototype for identification. Conclusions : For practical use of facial feature in Sasang Constitution Diagnosis, 1) Standardization of diagnosis through establishing Sasang Medical Diagnosis clinical protocol must be preceded. After the standardization, practical purpose and direction of facial form in general may be decided. 2) Information on high quality facial form of constitutional and conditional patients must be collected to form extensive database. 3) Subdivided symptomatology, as well as Sasang Constitution must be considered for diagnosis in order for diagnosis technique to acquire clinical practicality.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1692-1700
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• 2009

This paper proposes the direction distribution of surface normal vectors as a feature descriptor of three-dimensional models. Proposed the feature descriptor handles rotation invariance using a principal component analysis(PCA) method, and performs mesh simplification to make it robust and nonsensitive against noise addition. Our method picks samples for the distribution of normal vectors to be proportional to the area of each polygon, applies weight to the normal vectors, and applies interpolation to enhance discrimination so that the information on the surface with less area may be less reflected on composing a feature descriptor. This research measures similarity between models with a L1-norm in the probability density histogram where the distances of feature descriptors are normalized. Experimental results have shown that the proposed method has improved the retrieval performance described in an average normalized modified retrieval rank(ANMRR) by about 17.2% and the retrieval performance described in a quantitative discrimination scale by 9.6%~17.5% as compared to the existing method.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.11
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• pp.789-794
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• 2013

A vehicle tracking system makes it possible to induce the vehicle movement path for avoiding traffic congestion and to prevent traffic accidents in advance by recognizing traffic flow, monitoring vehicles, and detecting road accidents. To track the vehicles effectively, those which appear in a sequence of video frames need to identified by extracting the features of each object in the frames. Next, the identical vehicles over the continuous frames need to be recognized through the matching among the objects' feature values. In this paper, we identify objects by binarizing the difference image between a target and a referential image, and the labelling technique. As feature values, we use the center coordinate of the minimum bounding rectangle(MBR) of the identified object and the averages of 1D FFT(fast Fourier transform) coefficients with respect to the horizontal and vertical direction of the MBR. A vehicle is tracked in such a way that the pair of objects that have the highest similarity among objects in two continuous images are regarded as an identical object. The experimental result shows that the proposed method outperforms the existing methods that use geometrical features in tracking accuracy.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.868-874
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• 2014

This paper proposes a novel mapping algorithm in Omni-directional Vision SLAM based on an obstacle's feature extraction using Lucas-Kanade Optical Flow motion detection and images obtained through fish-eye lenses mounted on robots. Omni-directional image sensors have distortion problems because they use a fish-eye lens or mirror, but it is possible in real time image processing for mobile robots because it measured all information around the robot at one time. In previous Omni-Directional Vision SLAM research, feature points in corrected fisheye images were used but the proposed algorithm corrected only the feature point of the obstacle. We obtained faster processing than previous systems through this process. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous $360^{\circ}$ panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we remove the feature points of the floor surface using a histogram filter, and label the candidates of the obstacle extracted. Third, we estimate the location of obstacles based on motion vectors using LKOF. Finally, it estimates the robot position using an Extended Kalman Filter based on the obstacle position obtained by LKOF and creates a map. We will confirm the reliability of the mapping algorithm using motion estimation based on fisheye images through the comparison between maps obtained using the proposed algorithm and real maps.