• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.394-402
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• 2011

We introduce the standard content identifier Universal Content Identifier (UCI) and a watermarking system that embeds UCI for the broadcast content distribution services. Our proposed UCI embedder is designed in consideration of integrating with the previously established broadcast system and protecting the illegal distribution of broadcast contents. Our goal is that when broadcast content is transmitted, 28 byte UCI is embedded imperceptibly in the content itself in real-time and the embedded UCI is successfully extracted not only in the typical format used in the broadcast content distribution service but also in the illegally distributed broadcast contents. Usually the illegally distributed contents are modified from the original by changing resolutions, frame rates, or adjusting colors. In this paper, we present a watermarking scheme that embeds 28 byte UCI in broadcast content in real-time while keeping the visual quality high and the embedded watermark robust enough to survive through the various modification. The experimental results show that the embedded UCI remains in the various modified versions of content and that the visual degradation by embedding is not noticeable.

• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.101-115
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• 2020

In this paper, big data analysis method was used to find out global trends in autonomous driving and to derive activate spatial information services. The applied big data was used in conjunction with news articles and patent document in order to analysis trend in news article and patents document data in spatial information. In this paper, big data was created and key words were extracted by using LDA (Latent Dirichlet Allocation) based on the topic model in major news on autonomous driving. In addition, Analysis of spatial information and connectivity, global technology trend analysis, and trend analysis and prediction in the spatial information field were conducted by using WordNet applied based on key words of patent information. This paper was proposed a big data analysis method for predicting a trend and future through the analysis of the connection between the autonomous driving field and spatial information. In future, as a global trend of spatial information in autonomous driving, platform alliances, business partnerships, mergers and acquisitions, joint venture establishment, standardization and technology development were derived through big data analysis.