• The Journal of the Acoustical Society of Korea
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• 제21권1E호
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• pp.31-41
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• 2002

This study aims at investigating the relationship between voice and the image information carried within the voice. Whenever we hear somebody talking, we form a mental image of the speaker. Is it accurate? Is there a relationship between the voice and the image triggered by the voice? To answer these questions, speech samples form 8 males and 8 females were recorded. Two photos were taken for each speaker: the whole body photo (W) with physical characteristics present, and the face close-ups (F) without much physical details revealed. 361 subjects were asked to match the voices with the corresponding photos. The results showed that 5 males and 5 f3males (with W) and 2 males and 4 females (with F) were correctly identified. More interestingly, however, even in the mismatches, there was a strong tendency for participants to agree on which voice should correspond to which photo. The participants also agreed much more readily on their favorite voice than on their favorite photo. It seems voice does carry certain information about the physical characteristics of the speaker in a consistent manner. These findings have some bearings on understanding the mechanism of speech production and perception as well as on improving speech technology.

• 기본간호학회지
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• 제18권4호
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• pp.452-462
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• 2011

Purpose: The purpose of this study was to examine the factors affecting body image among undergraduate students. Method: The research design for this study was a descriptive survey design using a convenience sampling. Data collection was done using self-report questionnaires with 319 undergraduate students located in 3 cities, Seoul, Gangneung and Seosan. Pearson correlation coefficients and hierarchical multiple regression with the SPSS Win 12.0 Program were used to analyze the data. Results: In the hierarchical multiple regression analysis, gender, height, weight and college major were controlled. Body surveillance and body shame significantly predicted 72.3% of appearance orientation. Sociocultural attitudes toward appearance and self-esteem significantly predicted 33.5% of appearance evaluation. Self-esteem and body surveillance significantly predicted 15.9% of health orientation. Self-esteem significantly predicted 23.3% of health evaluation. Conclusion: Findings from this study provide a comprehensive understanding of body image and related factors in undergraduate students in Korea. However, further study with a larger random sample and more a detailed research design is necessary.

• Journal of applied mathematics & informatics
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• 제27권1_2호
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• pp.175-182
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• 2009

Microscopic imaging system often requires the algorithm to adjust location of camera lenses automatically in machine level. An effort to detect the best focal point is naturally interpreted as a mathematical inverse problem [1]. Following Wiener's point of view [2], we interpret the focus level of images as the quantified factor appeared in image degradation model: g = $f{\ast}H+{\eta}$, a standard mathematical model for understanding signal or image degradation process [3]. In this paper we propose a simple, very fast and robust method to compare the degradation parameters among the multiple images given by introducing outlier analysis of histogram.

• Communications for Statistical Applications and Methods
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• 제26권6호
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• pp.591-610
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• 2019

Deep Learning is one of the machine learning methods to find features from a huge data using non-linear transformation. It is now commonly used for supervised learning in many fields. In particular, Convolutional Neural Network (CNN) is the best technique for the image classification since 2012. For users who consider deep learning models for real-world applications, Keras is a popular API for neural networks written in Python and also can be used in R. We try examine the parameter estimation procedures of Deep Neural Network and structures of CNN models from basics to advanced techniques. We also try to figure out some crucial steps in CNN that can improve image classification performance in the CIFAR10 dataset using Keras. We found that several stacks of convolutional layers and batch normalization could improve prediction performance. We also compared image classification performances with other machine learning methods, including K-Nearest Neighbors (K-NN), Random Forest, and XGBoost, in both MNIST and CIFAR10 dataset.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.390-395
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• 1999

Ocean Scanning Multispectral Imager (OSMI) is a payload on the Korean Multi-purpose SATellite (KOMPSAT) to perform worldwide ocean color monitoring for the study of biological oceanography KOMPSAT will be launched in the middle of November this year. The radiometric performance of OSMI is analyzed for various gain settings in the viewpoint of the instrument developer for OSMI calibration and application based on its ground performance measurement data for 8 primary spectral bands of OSMI. The radiometric response linearity and dynamic range are analyzed for the image radiometric calibration and the estimation of OSMI image quality for the ocean remote sensing area. The dynamic range is compared with the nominal input radiance for the ocean and the land. The noise equivalent radiance (NER) corresponding to the instrument radiometric noise is compared with the radiometric resolution of signal digitization (1-count equivalent radiance). The best gain setting of OSMI for ocean monitoring is recommended. This analysis is considered to be useful for the OSMI mission and operation planning, the OSMI image data calibration, and users' understanding about OSMI image quality.

• 복식
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• 제62권4호
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• pp.123-135
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• 2012

The purpose of this study was to make marketing strategies for Korean fashion companies that wish to enter into foreign markets. In-depth-interviews along with documentary research were performed on consumers who lived in Italy. The interviews were executed from May to December 2010. The results of research were as follows. The general image of Korea was at a high level. Therefore, the general and economical image of Korea had a significant impact on product evaluation. However, the Italian consumer had only a little understanding about the Korean fashion brand and product. This was so because the Korean fashion companies did not appear in the Italian fashion market. However, they were accustomed to using products of Samsung and LG. Therefore, the economical image of Korea is necessary to facilitate the official entrance of fashion companies in the Italian market as well as the global market.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1408-1411
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• 2002

In this paper, we propose a method that converts motion vectors on MPEG coded domain as a uniform set, independent of the frame type and the direction of prediction, and directly utilizes these normalized motion vectors for understanding video contents. This frame-type-independent motion vectors are utilized as feature information for image retrieval or moving object tracking on compressed domain. By simulation, we evaluate the effectiveness of the proposed method and compare its performance to the conventional method.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.248-250
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• 2003

An automatic approach and strategy for extracting building information from aerial images using combined image analysis and interpretation techniques is described in this paper. A dense DSM is obtained by stereo image matching. Multi-band classification, DSM, texture segmentation and Normalised Difference Vegetation Index (NDVI) are used to reveal building interest areas. Then, based on the derived approximate building areas, a shape modelling algorithm based on the level set formulation of curve and surface motion has been used to precisely delineate the building boundaries. Data fusion, based on the Dempster-Shafer technique, is used to interpret simultaneously knowledge from several data sources of the same region, to find the intersection of propositions on extracted information derived from several datasets, together with their associated probabilities. A number of test areas, which include buildings with different sizes, shape and roof colour have been investigated. The tests are encouraging and demonstrate that the system is effective for building extraction, and the determination of more accurate elevations of the terrain surface.

• 한국의학물리학회지:의학물리
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• 제32권1호
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• pp.1-17
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• 2021

The evolution of X-ray computed tomography (CT) has been based on the discovery of X-rays, the inception of the Radon transform, and the development of X-ray digital data acquisition systems and computer technology. Unlike conventional X-ray imaging (general radiography), CT reconstructs cross-sectional anatomical images of the internal structures according to X-ray attenuation coefficients (approximate tissue density) for almost every region in the body. This article reviews the essential physical principles and technical aspects of the CT scanner, including several notable evolutions in CT technology that resulted in the emergence of helical, multidetector, cone beam, portable, dual-energy, and phase-contrast CT, in integrated imaging modalities, such as positron-emission-tomography-CT and single-photon-emission-computed-tomography-CT, and in clinical applications, including image acquisition parameters, CT angiography, image adjustment, versatile image visualizations, volumetric/surface rendering on a computer workstation, radiation treatment planning, and target localization in radiotherapy. The understanding of CT characteristics will provide more effective and accurate patient care in the fields of diagnostics and radiotherapy, and can lead to the improvement of image quality and the optimization of exposure doses.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권2호
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• pp.524-543
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• 2022

Correct facade image parsing is essential to the semantic understanding of outdoor scenes. Unfortunately, there are often various occlusions in front of buildings, which fails many existing methods. In this paper, we propose an end-to-end deep network for facade parsing with occlusions. The network learns to decompose an input image into visible and invisible parts by occlusion reasoning. Then, a context aggregation module is proposed to collect nonlocal cues for semantic segmentation of the visible part. In addition, considering the regularity of man-made buildings, a repetitive pattern completion branch is designed to infer the contents in the invisible regions by referring to the visible part. Finally, the parsing map of the input facade image is generated by fusing the results of the visible and invisible results. Experiments on both synthetic and real datasets demonstrate that the proposed method outperforms state-of-the-art methods in parsing facades with occlusions. Moreover, we applied our method in applications of image inpainting and 3D semantic modeling.