• Journal of IKEEE
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• v.23 no.2
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• pp.358-363
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• 2019

In this paper, we implemented a welfare system for the elderly living alone, disabled, or babies to provide fast incident response in case of emergency situations. The proposed system can quickly recognize emergency situations using heart rate sensors and real-time image sharing. The sensors attached on a wrist band monitor the heart rate along with relevant bio signals of clients and send alarms to guardians in the emergency situations. At the same time, the real-time image signals are captured using OpenCV and sent to the guardians in order to give the exact information for fast and appropriate response to handle the situation. In the proposed system, the camera works only in the emergency situations so as to provide enough privacy to the client's every day life.

• Journal of the Korean Society of Clothing and Textiles
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• v.43 no.6
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• pp.808-824
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• 2019

This study analyzes the values of vintage in Korean fashion prosumer's activities and elevates the values as one characteristic of Korean modern fashion. The methodology included literary and empirical studies as well as prosumer and modern Korean vintage fashion literary studies. In-depth interviews were done to analyze the values of vintage in fashion prosumer's activities. The values of vintage fashion for Millennials are creative activities based on public interest, expanded reproducing through sharing daily looks and self-expression through the scarcity of vintage clothing. Prosumer characteristics are self-satisfaction and sharing. Fashion prosumer's vintage trends are new-tro, communication, cultural complex, and sharing of daily life. The formativeness in fashion prosumer's activities are heritage, text, activity and image. The meanings are creation, communication, experience and sharing. Fashion prosumers are developing the new genre of 'vintage fashion activity'; in addition, values towards vintage fashion activity are also drawing international interest.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.99-104
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• 1998

Application sharing is the ability to use existing applications, such as Excel or MS-Word, during a group session without modification. In this paper, we present the design and implementation of an application sharing system, called ShareIt, which enable users to share arbitrary MS-Windows applications under the Win 3.1/95/NT and X window system, and evaluation of the system performance. To share an application, the image of the application window is captured and transmitted to other sites. With the use of the window capturing method, ShareIt allows any MS-Windows application to be shared regardless of not only the window systems but also the version-up of window systems.

• Journal of Information Management
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• v.40 no.1
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• pp.47-67
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• 2009

Digital literacy is an important factor in the discourses on the knowledge sharing on the campus. This article analyzed the impact of digital literacy of knowledge-sharing capabilities in the university. As a result, digital literacy was found to significantly affect student knowledge-sharing capabilities in the university studied. Results show that video and animation literacy is the most influential factor and image literacy is the second-most influential factor for student knowledge-sharing. Those results can be used as a framework for developing digital literacy program.

• Journal of Biosystems Engineering
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• v.29 no.1
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• pp.71-78
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• 2004

Real time and robust algorithm to extract the features of watermelon was developed from the remotely transmitted image of the watermelon. Features of the watermelon at the cultivation site such as size and shape including position are crucial to the successful tole-robotic operation and development of the cultivation data base. Algorithm was developed based on the concept of task sharing between the computer and the operator utilizing man-computer interface. Task sharing was performed based on the functional characteristics of human and computer. Identifying watermelon from the image transmitted from the cultivation site is very difficult because of the variable light condition and the complex image contents such as soil, mulching vinyl, straws on the ground, irregular leaves and stems. Utilizing operator's teaching through the touch screen mounted on the image monitor, the complex time consuming image processing process and instability of processing results in the watermelon identification has been avoided. Color and brightness characteristics were analyzed from the image area specified by the operator's teaching. Watermelon segmentation was performed using the brightness and color distribution of the specified imae processing area. Modified general Hough transform was developed to extract the shape, major and minor axes, and the position, of the watermelon. It took less than 100 msec of the image processing time, and was a lot faster than conventional approach. The proposed method showed the robustness and practicability in identifying watermelon from the wireless transmitted color image of the cultivation site.

• ETRI Journal
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• v.37 no.5
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• pp.979-989
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• 2015

Recently, Hou and others introduced a (2, n) block-based progressive visual cryptographic scheme (BPVCS) in which image blocks can be gradually recovered step by step. In Hou and others' (2, n)-BPVCS, a secret image is subdivided into n non-overlapping image blocks. When t ($2{\leq}t{\leq} n$) participants stack their shadow images, all the image blocks associated with these t participants will be recovered. However, Hou and others' scheme is only a simple 2-out-of-n case. In this paper, we discuss a general (k, n)-BPVCS for any k and n. Our main contribution is to give two constructions (Construction 1 and Construction 2) of this general (k, n)-BPVCS. Also, we theoretically prove that both constructions satisfy a threshold property and progressive recovery of the proposed (k, n)-BPVCS. For k = 2, Construction 1 is reduced to Hou and others' (2, n)-BPVCS.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.31-33
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• 2009

Face detection using AdaBoost algorithm is capable of processing images rapidly while having high detection rates. It seemed to be the fastest and the most robust and it is still today. Many improvements or extensions of this method have been proposed. However, previous approaches only deal with upright faces. They suffer from limited discriminant capability for rotated faces as these methods apply the same features for both upright and rotated faces. To solve this problem, it is necessary that we rotate input images or make independently trained detectors. However, this can be slow and can require a lot of training data, since each classifier requires the computation of many different image features. This paper proposes a robust algorithm for finding rotated faces within an image. It reduces the computational and sample complexity, by finding common features that can be shared across the classes. And it will be able to apply with multi-class object detection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3401-3420
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• 2018

Pixel expansion and contrast are two major performance parameters for visual cryptography scheme (VCS), which is a type of secret image sharing. Random Grid (RG) is an alternative approach to solve the pixel expansion problem. Chen and Tsao proposed the first (k, n) RG-based VCS, and then Guo et al., Wu et al., Shyu, and Yan et al. significantly improved the contrast in recent years. However, the investigations on improving the contrast of threshold RG-based VCS are not sufficient. In this paper, we develop a contrast-improved algorithm for (k, n) RG-based VCS. Theoretical analysis and experimental results demonstrate that the proposed algorithm outperformers the previous threshold algorithms with better visual quality and a higher accuracy of contrast.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.268-283
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• 2020

The purpose of this study was to examine the effect of exposure to body image in media and bullet screen on weight loss intention by specifically focusing on Bilibili, a video sharing website of China. For the study, a 3 (Social viewing: no bullet screen vs. complimentary bullet screen vs. critical bullet screen) x 2 (Body image in media: ideal vs. realistic) between-subjects factorial design was conducted. A total of 310 Chinese women in their 20s were recruited to participate in an experimental survey. The main results showed that viewing the ideal body image with the complimentary bullet screen and realistic body image with the critical bullet screen strengthened the participants' intention on weight loss. Finally, the interaction effect of social viewing and the types of bullet screen were examined. The higher weight-loss intention was revealed when social viewing was conducted with the complimentary bullet screen of the ideal image. The results of this study can enhance the understanding of the bullet screen as a type of social viewing and its effect on user behavior intention.

• Journal of Information Science Theory and Practice
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• v.6 no.2
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• pp.46-61
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• 2018

The mobile social networking application Instagram is a well-known platform for sharing photos and videos. Since it is folksonomy-oriented, it provides the possibility for image indexing and knowledge representation through the assignment of hashtags to posted content. The purpose of this study is to analyze how Instagram users tag their pictures regarding different kinds of picture and hashtag categories. For such a content analysis, a distinction is made between Food, Pets, Selfies, Friends, Activity, Art, Fashion, Quotes (captioned photos), Landscape, and Architecture image categories as well as Content-relatedness (ofness, aboutness, and iconology), Emotiveness, Isness, Performativeness, Fakeness, "Insta"-Tags, and Sentences as hashtag categories. Altogether, 14,649 hashtags of 1,000 Instagram images were intellectually analyzed (100 pictures for each image category). Research questions are stated as follows: RQ1: Are there any differences in relative frequencies of hashtags in the picture categories? On average the number of hashtags per picture is 15. Lowest average values received the categories Selfie (average 10.9 tags per picture) and Friends (average 11.7 tags per picture); for highest, the categories Pet (average 18.6 tags), Fashion (average 17.6 tags), and Landscape (average 16.8 tags). RQ2: Given a picture category, what is the distribution of hashtag categories; and given a hashtag category, what is the distribution of picture categories? 60.20% of all hashtags were classified into the category Content-relatedness. Categories Emotiveness (about 4.38%) and Sentences (0.99%) were less often frequent. RQ3: Is there any association between image categories and hashtag categories? A statistically significant association between hashtag categories and image categories on Instagram exists, as a chi-square test of independence shows. This study enables a first broad overview on the tagging behavior of Instagram users and is not limited to a specific hashtag or picture motive, like previous studies.