• Journal of Broadcast Engineering
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• v.28 no.1
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• pp.42-54
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• 2023

It is an important issue to compress huge holographic data in a digital format. In particular, research on the compression of phase-only holograms for commercialization is noteworthy. Conventional video coding standards optimized for natural images are not suitable for compressing phase signals, and neural network-based compression model that can be optimized for phase signals can achieve high performance, but has a memory issue in learning high-resolution holographic data. In this paper, we show that by applying a block-based learned image compression model that can solve memory problems to phase-only holograms, the proposed method can demonstrate significant performance improvement over standard codecs even under the same conditions as block-based. Block-based learned compression model can provide compatibility with conventional standard codecs, solve memory problems, and can perform significantly better against phase-only hologram compression.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.10
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• pp.421-428
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• 2021

The High Efficiency Image File Format (HEIF) is an MPEG-developed image format that utilizes the video codec H.265 to store still screens in a single image format. The iPhone has been using HEIF since 2017, and Android devices such as the Galaxy S10 have also supported the format since 2019. The format can provide images with good compression rates, but it has a complex internal structure and lacks significant compatibility between devices and software, making it not popular to replace commonly used JPEG (or JPG) files. However, despite the fact that many devices are already using HEIF, digital forensics research regarding it is lacking. This means that we can be exposed to the risk of missing potential evidence due to insufficient understanding of the information contained inside the file during digital forensics investigations. Therefore, in this paper, we analyze the HEIF formatted photo file taken on the iPhone and the motion photo file taken on the Galaxy to find out the information and features contained inside the file. We also investigate whether or not the software we tested support HEIF and present the requirement of forensic tools to analyze HEIF.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.327-333
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• 2021

The purpose of this study is to explore what elements and measures are necessary to grasp the content influence and competitiveness of each OTT platform, which is difficult to measure only with the existing TV broadcast ratings indicator, on the same basis. In this study, based on the RACOI, the daily Top 10 list provided by Netflix was scored to determine the correlation with the viewers' reaction to TV dramas, and a meaningful comparison criterion index was derived. Based on this, the study tried to analyze the share of content provided by the top 3 OTT platforms in Korea. Spearman's correlation analysis was performed for each indicator of RACOI and the Netflix popularity score. It was confirmed that the Netflix popularity score was correlated with the digital video views indicator of RACOI. As a result of analyzing the platforms, it was found that the popularity of the content provided by Netflix and Tving was relatively high. This study did not secure the company's sales data, and there is a limitation in that long-term tracking analysis could not be performed. However, the study extracted the viewer response indicators of TV that are correlated with popularity within Netflix. It is valuable as a basic study of an extended study that compares and confirms the long-term impact of content provided by each OTT platform in the future.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.367-378
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• 2014

The purpose of this study was to explore the factors related to internet addiction in college student of Korea. Methods: From November 19, 2012 until December 14, 2012, 300 college students from one of the universities located at K city were surveyed. This study is a cross-sectional survey of college students in K city, and data was collected through self-report questionnaires. Data was analyzed by Fisher's exact test, independent t-test to identify different according to addiction group, and logistic regression analysis in order to factors related to on health behavior, sexual behavior and mental health of among college students. According to results, factors related to risk of addiction were lower frequency of exercise (p<0.05), no eat breakfast for 2 day (p<0.05), porno magazine/porno video contact pornography (p<0.05), subjective happiness index (p<0.05), and suicidal Ideation (p<0.05). This study suggest that exercise, regular diet, important of reproductive health, subjective happiness index and Suicidal Ideation are associated with internet addiction in College student. It is necessary to develop some preventive programs for those of internet addiction.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.571-579
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• 2020

The purpose of the study was to explore modern people's emotion regarding sex commercialization related to the abolition of grid girl. To collect data, based on 'reply journalism', this study collected 15 blogs, 10 online cafe contents, 1 youtube video clip, and 364 replies associated with the three online contents. To analyze the data, interpretive text analysis was utilized and the following results were obtained. As results, the analysis on the replies shows that the most strong emotion of the modern people regarding the abolition of grid girl is anti-feminism that includes hatred toward feminists and even females, criticism on feminism, and notion of 'women's enemy is women themselves'. In addition, sympathy toward racing models who lost their jobs, requirement of same abolition to the people with similar occupations, spatial separation between men and women, and consent on the abolition of racing models were found. Unlike the feminists' emotion regarding sex commercialization and racing models, modern people's emotion was different from them. Rather, ordinary people have doubted and even criticized on the rationales of feminism. Unlike feminists' notion about sex commercialization of racing models, these results imply that social image of racing models has changed and wish their position is respected as an ordinary occupation, without issues of sex commercialization.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.183-190
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• 2016

This paper proposes algorithm to reduce the computing time in a neural network that reduces transmission of data for tracking mobile objects in surveillance networks in terms of detection and communication load. Object Detection can be defined as follows : Given image sequence, which can forom a digitalized image, the goal of object detection is to determine whether or not there is any object in the image, and if present, returns its location, direction, size, and so on. But object in an given image is considerably difficult because location, size, light conditions, obstacle and so on change the overall appearance of objects, thereby making it difficult to detect them rapidly and exactly. Therefore, this paper proposes fast and exact object detection which overcomes some restrictions by using neural network. Proposed system can be object detection irrelevant to obstacle, background and pose rapidly. And neural network calculation time is decreased by reducing input vector size of neural network. Principle Component Analysis can reduce the dimension of data. In the video input in real time from a CCTV was experimented and in case of color segment, the result shows different success rate depending on camera settings. Experimental results show proposed method attains 30% higher recognition performance than the conventional method.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.475-483
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• 2021

The purpose of this study is to identify the temporal and spatial characteristics of pass accuracy by utilizing the second processing data and official records collected from the 2018 FIFA World Cup Russia video data. For a total of 128 games, the success rate of passes based on the results of the game, passing time, and passing position was two-way ANOVA with repeated measure. The results showed no difference between winning and losing groups, and no interaction effects were found for passing time and location. The difference in passing time was high in the first half, with the highest success rate in the middle of the first half (79.2%) and the middle of the second half (77.9%) in the 15~30 minutes and the 60~75 minutes. Pass success rates were in the order of defense-midfield area (83.9%), midfield-attack area (81.7%), defense area (70.6%) and attack area (61.1%). In conclusion, there was no difference in the passing success rate of the winning and losing teams depending on the characteristics of the relative competitive strength of the World Cup games, and it is believed that follow-up research is needed to analyze the game contents rather than the factors of the winning and losing in the future.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1076-1084
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• 2019

In this paper, we introduced a system that extracts metadata by recognizing characters and objects in media using deep learning technology. In the field of broadcasting, multimedia contents such as video, audio, image, and text have been converted to digital contents for a long time, but the unconverted resources still remain vast. Building media archives requires a lot of manual work, which is time consuming and costly. Therefore, by implementing a deep learning-based metadata generation system, it is possible to save time and cost in constructing media archives. The whole system consists of four elements: training data generation module, object recognition module, character recognition module, and API server. The deep learning network module and the face recognition module are implemented to recognize characters and objects from the media and describe them as metadata. The training data generation module was designed separately to facilitate the construction of data for training neural network, and the functions of face recognition and object recognition were configured as an API server. We trained the two neural-networks using 1500 persons and 80 kinds of object data and confirmed that the accuracy is 98% in the character test data and 42% in the object data.

• Science of Emotion and Sensibility
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• v.11 no.4
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• pp.575-588
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• 2008

This study is to inquire respective patterns of mental models caused by wrongful usages which can be experienced when a user who is used to a keypad-based mobile phone starts using a touch screen mobile phone and to find out the features of the user's logical process of correcting such wrongful usages to a new mental model. In addition, design improvement to be considered for easy generation of the mental model regarding touch screen mobile phones was reviewed in this study. We set up test subjects for the most frequently used seven high priority functions among touch screen phone functions and carried out the subject assessment together with interview surveys after the video observation experiment. Our test results show that test subjects who were used to keypad-based mobile phones tend to use operation knowledge related to the computer operational system(Window) or the web browse, navigation including Tap or Double Tap in order to correct the mental model when a wrongful usage is made. In addition, the result of comparison and analysis of the subject assessment and the video observation experiment data shows that wrongful usages of touch screen mobile phones mostly occurred in the field of 'information feedback' and 'navigation' among mobile phone components.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.3
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• pp.249-255
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• 2011

The free-stereo mosaics image without GPS/INS and ground control data can be generated by using relative orientation parameters on the 3D model coordinate system. Its origin is located in one reference frame image. A 3D coordinate calculated by conjugate points on the free-stereo mosaic images is represented on the 3D model coordinate system. For determining 3D coordinate on the 3D absolute coordinate system utilizing conjugate points on the free-stereo mosaic images, transformation methodology is required for transforming 3D model coordinate into 3D absolute coordinate. Generally, the 3D similarity transformation is used for transforming each other 3D coordinates. Error of 3D model coordinates used in the free-stereo mosaic images is non-linearly increased according to distance from 3D model coordinate and origin point. For this reason, 3D model coordinates used in the free-stereo mosaic images are difficult to transform into 3D absolute coordinates by using linear transformation. Therefore, methodology for transforming nonlinear 3D model coordinate into 3D absolute coordinate is needed. Also methodology for resampling the free-stereo mosaic image to the geo-stereo mosaic image is needed for overlapping digital map on absolute coordinate and stereo mosaic images. In this paper, we propose a 3D non-linear transformation for converting 3D model coordinate in the free-stereo mosaic image to 3D absolute coordinate, and a 2D non-linear transformation based on 3D non-linear transformation converting the free-stereo mosaic image to the geo-stereo mosaic image.