• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.113-130
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• 2004

Most multimedia data contain text to emphasize the meaning of the data, to present additional explanations about the situation, or to translate different languages. But, the left makes it difficult to reuse the images, and distorts not only the original images but also their meanings. Accordingly, this paper proposes a support vector machines (SVMs) and spatiotemporal restoration-based approach for automatic text detection and removal in video sequences. Given two consecutive frames, first, text regions in the current frame are detected by an SVM-based texture classifier Second, two stages are performed for the restoration of the regions occluded by the detected text regions: temporal restoration in consecutive frames and spatial restoration in the current frame. Utilizing text motion and background difference, an input video sequence is classified and a different temporal restoration scheme is applied to the sequence. Such a combination of temporal restoration and spatial restoration shows great potential for automatic detection and removal of objects of interest in various kinds of video sequences, and is applicable to many applications such as translation of captions and replacement of indirect advertisements in videos.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.2
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• pp.29-42
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• 2024

As a global response to climate and biodiversity challenges, there is an emphasis on the conservation and restoration of ecosystems that can simultaneously reduce carbon emissions and enhance biodiversity. This study comprised a text analysis and keyword extraction of 1,100 research papers addressing nature restoration in Korea, aiming to provide a quantative and systematic evaluation of domestic research trends in this field. To discern the major research topics of these papers, topic modeling was applied and correlations were established through network analysis. Research on nature restoration exhibited a mainly upward trend in 2002-2022 but with a slight recent decline. The most common keywords were "species," "forest," and "water". Research topics were broadly classified into (1) predictions of habitat size and species distribution, (2) the conservation and utilization of natural resources in urban areas, (3) ecosystems and landscape managements in protected areas, (4) the planting and growth of vegetation, and (5) habitat formation methods. The number of studies on nature restoration are increasing across various domains in Korea, with each domain experiencing professional development.

• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.205-210
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• 2008

A new approach is proposed for restoration of corrupted regions and segmentation in natural text images. The challenge is to fill in the corrupted regions on the basis of color feature analysis by second order symmetric stick tensor. It is show how feature analysis can benefit from analyzing features using tensor voting with chromatic and achromatic components. The proposed method is applied to text images corrupted by manifold types of various noises. Firstly, we decompose an image into chromatic and achromatic components to analyze images. Secondly, selected feature vectors are analyzed by second-order symmetric stick tensor. And tensors are redefined by voting information with neighbor voters, while restore the corrupted regions. Lastly, mode estimation and segmentation are performed by adaptive mean shift and separated clustering method respectively. This approach is automatically done, thereby allowing to easily fill-in corrupted regions containing completely different structures and surrounding backgrounds. Applications of proposed method include the restoration of damaged text images; removal of superimposed noises or streaks. We so can see that proposed approach is efficient and robust in terms of restoring and segmenting text images corrupted.

• Proceedings of the Zoological Society Korea Conference
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• 2001.10a
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• pp.268.2-268
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• 2001

No Abstract, See Full Text

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.740-753
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• 2023

Text recognition in natural scene images is a challenging problem in computer vision. The accurate identification of ship number characters can effectively improve the level of ship traffic management. However, due to the blurring caused by motion and text occlusion, the accuracy of ship number recognition is difficult to meet the actual requirements. To solve these problems, this paper proposes a dual-branch network based on the CRNN identification network. The network couples image restoration and character recognition. The CycleGAN module is used for blur restoration branch, and the Pix2pix module is used for character occlusion branch. The two are coupled to reduce the impact of image blur and occlusion. Input the recovered image into the text recognition branch to improve the recognition accuracy. After a lot of experiments, the model is robust and easy to train. Experiments on CTW datasets and real ship maps illustrate that our method can get more accurate results.

• Proceedings of the Zoological Society Korea Conference
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• 2001.10a
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• pp.124.1-124
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• 2001

No Abstract, See Full Text

• Proceedings of the Zoological Society Korea Conference
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• 2001.10a
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• pp.138.3-138
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• 2001

No Abstract, See Full Text

• Proceedings of the Zoological Society Korea Conference
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• 2001.10a
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• pp.230.1-230
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• 2001

No Abstract, See Full Text

• The Korean Journal of Quaternary Research
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• v.15 no.2
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• pp.119-127
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• 2001

No Abstract, See Full Text

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.2 no.4
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• pp.247-258
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• 2021

To understand restoration and conservation projects conducted in Korea for endangered freshwater fishes and amphibians/reptiles, information about Request for Protocols-related studies on restoration, breeding, and release were collected. Trends of studies were visualized via word clouds and VOSviewer program using a text mining technique. Analysis of restoration projects for endangered freshwater fishes elucidated that most research studies conducted to date were focused on genetics and release through captive breeding that could be classified into captive breeding and habitat environments. As for research projects related to amphibians/reptiles, monitoring projects had the highest number, followed by genetic, translocation, and monitoring studies. In addition, restoration projects for amphibians/reptiles included a large number of post-capture translocation projects. Thus, many projects were confirmed by public institutions rather than by the Ministry of Environment. Network analysis revealed that it was largely classified into capture, translocation, and Kaloula borealis. Based on these results, limitations, achievements, and challenges associated with projects conducted thus far are highlighted. Research directions for future restoration and conservation of endangered freshwater fishes and amphibians/reptiles in South Korea are also suggested.