• Journal of Advanced Marine Engineering and Technology
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• v.23 no.2
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• pp.259-269
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• 1999

A new algorithm for measuring 3-D velocity components of high speed flows were developed using a digital image processing technique. The measuring system consists of three CCD cameras an optical instrument called AOM a digital image grabber and a host computer. The images of mov-ing particles arranged spatially on a rotation plate are taken by two or three CCD cameras and are recorderd onto the image grabber or a video tape recoder. The three-dimensionl velocity com-ponents of the particles are automatically obtained by the developed algorithm In order to verify the validity of this technique three-dimensional velocity data sets obtained from a computer simu-lation of a backward facing step flow were used as test data for the algorithm. an uncertainty analysis associated with the present algorithm is systematically evaluated, The present technique is proved to be used as a tookl for the measurement of unsteady three-dimensional fluid flows.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.59-61
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• 2018

Highly compressed images typically not only have low resolution, but are also affected by compression artifacts. Performing image super-resolution (SR) directly on highly compressed image would simultaneously magnify the blocking artifacts. In this paper, a SR method based on deep learning is proposed. The method is an end-to-end trainable deep convolutional neural network which performs SR on compressed images so as to reduce compression artifacts and improve image resolution. The proposed network is divided into compression artifacts removal (CAR) part and SR reconstruction part, and the network is trained by three-step training method to optimize training procedure. Experiments on JPEG compressed images with quality factors of 10, 20, and 30 demonstrate the effectiveness of the proposed method on commonly used test images and image sets.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.4
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• pp.75-90
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• 2013

Given the context that users are actively using social media with multimedia embedded information, the purpose of this study is to demonstrate how images are used within Twitter messages, especially in influential and favorited messages. In order to achieve the purpose of this study, the top 200 influential and favorited messages with images were selected out of 1,589 tweets related to "Boston bombing" in April 2013. The characteristics of the message, image use, and user are analyzed and compared. Two phases of the analysis were conducted on three data sets containing the top 200 influential messages, top 200 favorited messages, and general messages. In the first phase, coding schemes have been developed for conducting three categorical analyses: (1) categorization of tweets, (2) categorization of image use, and (3) categorization of users. The three data sets were then coded using the coding schemes. In the second phase, comparison analyses were conducted among influential, favorited, and general tweets in terms of tweet type, image use, and user. While messages expressing opinion were found to be most favorited, the messages that shared information were recognized as most influential to users. On the other hand, as only four image uses - information dissemination, illustration, emotive/persuasive, and information processing - were found in this data set, the primary image use is likely to be data-driven rather than object-driven. From the perspective of users, the user types such as government, celebrity, and photo-sharing sites were found to be favorited and influential. An improved understanding of how users' image needs, in the context of social media, contribute to the body of knowledge of image needs. This study will also provide valuable insight into practical designs and implications of image retrieval systems or services.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.25-36
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• 2014

Multispectral image classification of individual tree species is often difficult because of the spectral similarity among species. In this study, we attempted to analyze the suitability of hyperspectral image to classify coniferous tree species. Several image sets and classification methods were applied and the classification results were compared with the ones from multispectral image. Two airborne hyperspectral images (AISA, CASI) were obtained over the study area in the Gwangneung National Forest. For the comparison, ETM+ multispectral image was simulated using hyperspectral images as to have lower spectral resolution. We also used the transformed hyperspectral data to reduce the data volume for the classification. Three supervised classification schemes (SAM, SVM, MLC) were applied to thirteen image sets. In overall, hyperspectral image provides higher accuracies than multispectral image to discriminate coniferous species. AISA-dual image, which include additional SWIR spectral bands, shows the best result as compared with other hyperspectral images that include only visible and NIR bands. Furthermore, MNF transformed hyperspectral image provided higher classification accuracies than the full-band and other band reduced data. Among three classifiers, MLC showed higher classification accuracy than SAM and SVM classifiers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2335-2340
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• 2009

This paper presents how to implement Markerless Augmented Reality and how to create and apply reference data sets. There are three parts related with implementation: setting camera, creation of reference data set, and tracking. To create effective reference data sets, we need a 3D model such as CAD model. It is also required to create reference data sets from various viewpoints. We extract the feature points from the mode1 image and then extract 3D positions corresponding to the feature points using ray tracking. These 2D/3D correspondence point sets constitute a reference data set of the model. Reference data sets are constructed for various viewpoints of the model. Fast tracking can be done using a reference data set the most frequently matched with feature points of the present frame and model data near the reference data set.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.204-207
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• 2009

This paper presents how to implement Markerless Augmented Reality and how to create and apply reference data sets. There are three parts related with implementation: setting camera, creation of reference data set, and tracking. To create effective reference data sets, we need a 3D model such as CAD model. It is also required to create reference data sets from various viewpoints. We extract the feature points from the model image and then extract 3D positions corresponding to the feature points using ray tracking. These 2D/3D correspondence point sets constitute a reference data set of the model. Reference data sets are constructed for various viewpoints of the model. Fast tracking can be done using a reference data set the most frequently matched with feature points of the present frame and model data near the reference data set.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.12
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• pp.1381-1388
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• 2014

This paper is proposed a wavelet-based the order statistics MAD(Median Absolute Deviation) method of SAR(Synthetic Aperture Radar) image for image enhancement. also The method of compared and defined the threshold the wavelet coefficients using MAD of the wavelet coefficients of the detail subbands was proposed to effectively image enhancement. In order to complement the disadvantage, the threshold of the proposed method sets up the image statistic and excludes the distortion. The hardware design is used FPGA of Xilinx and DSP system for the image enhancement and compressed encoding of the proposed algorithm. Therefore the proposed method is totally verified by comparing with the several other images.

• Journal of Korean Dental Science
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• v.13 no.1
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• pp.28-34
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• 2020

Purpose: The purpose of this study was to investigate the influence of different implant computer software on the accuracy of image registration between radiographic and optical scan data. Materials and Methods: Cone-beam computed tomography and optical scan data of a partially edentulous jaw were collected and transferred to three different computer softwares: Blue Sky Plan (Blue Sky Bio), Implant Studio (3M Shape), and Geomagic DesignX (3D systems). In each software, the two image sets were aligned using a point-based automatic image registration algorithm. Image matching error was evaluated by measuring the linear discrepancies between the two images at the anterior and posterior area in the direction of the x-, y-, and z-axes. Kruskal-Wallis test and a post hoc Mann-Whitney U-test with Bonferroni correction were used for statistical analyses. The significance level was set at 0.05. Result: Overall discrepancy values ranged from 0.08 to 0.30 ㎛. The image registration accuracy among the software was significantly different in the x- and z-axes (P=0.009 and <0.001, respectively), but not different in the y-axis (P=0.064). Conclusion: The image registration accuracy performed by a point-based automatic image matching could be different depending on the computer software used.

• Journal of the Korean Society of Costume
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• v.58 no.6
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• pp.54-68
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• 2008

The purpose of this study is to investigate the effect of dot pattern size(0.8, 1.8, 2.5, 5, 8), color combination(BG/R, Y/B), area-ratio on image formation. Sets of stimulus and response scales(7 point semantic) were used as experimental materials. The stimuli were 20 color pictures manipulated with the combination of dot pattern size, color combination, and area-ratio using computer simulation. The subjects were 240 female undergraduates living in Gyeongnam-do. Image factor of the stimulus was composed of 5 different components, visibility, attractiveness, cuteness, stability and high class image. In the cuteness, color combination, dot pattern size showed independent effect. In the stability, area-ratio, dot pattern size showed independent effect. Interaction effects of color and area-ratio combination was significant on cuteness. For visibility image 8cm yellow dot/blue background, for attractiveness image BG/R coloration, for cuteness image Y/B coloration and for stability image 0.8cm yellow dot/blue background were effective. According to the variation of dot pattern size, color combination and area-ratio, it was investigated that the images for a dress wearer were expressed diversely, were shown differently in image dimensions, and could be produced to different images.

• Communications of the Korean Mathematical Society
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• v.33 no.4
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• pp.1321-1329
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• 2018

In this paper, we compare the dimension of a constructible set with the dimension of its inverse image under morphisms of finite type of noetherian Jacobson schemes.