• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.10
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• pp.120-129
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• 1996

This paper presents an efficient block segmentation and classification using the edge information of the document image. We extract four prominent features form the edge gradient and orientaton, all of which, and thereby the block clssifications, are insensitive to the background noise and the brightness variation of of the image. Using these four features, we can efficiently classify a document image into the seven categrories of blocks of small-size letters, large-size letters, tables, equations, flow-charts, graphs, and photographs, the first five of which are text blocks which are character-recognizable, and the last two are non-character blocks. By introducing the clumn interval and text line intervals of the document in the determination of th erun length of CRLA (constrained run length algorithm), we can obtain an efficient block segmentation with reduced memory size. The simulation results show that the proposed algorithm can rigidly segment and classify the blocks of the documents into the above mentioned seven categories and classification performance is high enough for all the categories except for the graphs with too much variations.

• Journal of the Korean Society of Costume
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• v.38
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• pp.101-122
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• 1998

The purpose of this study is to define the fundamentals of one symbolic concept, so calles vestment-sign, based on the logical relationship of sign system about the trichotomy by charles S. Peice's sign concept for the communication system of meaning in the non-linguistic image domain. To prove the argument of vestment-sign, I selected 3 type of vestment language by styliste, Elsa Schiaparel-li. The third image vestmental chosen here, titled“Larme-Illusion(1938)”,printed by Salvad-or Dali will produce one symbolic proposition as a logical result which is generated and developed through the interpretation of other images. First of all the text, which is manifested by Elsa Schiaparelli's first image vestmental, tit-led“Notation Musical(1937)”and is symbolized as one category in the representation of the form, is regarded symbolic and metaphorical from a standpoint that the title and the meaning is connected to the form. The second image vestment, titled“Ruches Noirs(1938)”represents externally splendid feminity man-ifested by the symbolic and metaphorical expression. And the purity of sensitivity aiming to humanity in the detail of the poetic feeling of naturalism makes us imagine the battle fild of furious sensitivity. Like as the result of the battle, the third image stimulated our eyesight with the“absence”of dressing function. The proposition of the text,《Death》which the third image delivers, constructs sign system to bring up a meaning with the disappearance of physical“signifier”. This establishment of the symbolic concept presents the etymological authority of symbol generation called“Design”.

• The Journal of Society for e-Business Studies
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• v.8 no.4
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• pp.33-51
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• 2003

The primary objectives of this study were, using data from Internet users in Korea, to determine users' preference of banner ad through two ad properties; ad presentation type (text vs. image) and ad content (product information vs. prize information) by incorporating the level of involvement into research design. Using within-group experimental design by means of subjects' web-based participation in the study, the study result showed that image-based banner ad was significantly preferred to text-based banner ad. It was found that the level of ad involvement had a significant impact on the preference of banner ads. Also it was found that image-based banner ad had a greater effect on ad preference than text-based banner ad in low involvement situation only, Finally, image-based banner ad was consistently preferred to text-based banner ad regardless of involvement level when the banner ad was product oriented. The study findings suggest that adoption decisions regarding banner ad presentation type and banner ad content should be based on the knowledge of both the level of consumer's ad involvement and the interactive effects between ad presentation and ad content.

• Journal of Korean Society of Rural Planning
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• v.27 no.3
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• pp.103-116
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• 2021

In this study, the characteristics of rural tourism image perceived by urban residents were analyzed through text analysis of blog data. In order to examine the images related to rural tourism, blog data written with the keyword "Gochang-gun travel" was used. LDA topic analysis, one of the text mining techniques, was used for the analysis. In the tourism image of Gochang-gun, 9 topics were derived, and 112 major places appeared. This was divided into 3 main activities and 5 object spaces through the review of keywords and the original text of blog data. As a result of the analysis, the traditional main resources of the region, Seonun mountain, Seonun temple, and Gochang-eup fortress, formed topic. On the other hand, world heritage such as dolmen and Ungok wetland did not appear as topic. In particular, the farms operated by the private sector form individual topics, and the theme farm can be seen as an important resource for tourism in Gochang-gun. Also, through the distribution of place keywords, it was possible to understand the characteristics of travel by region and the usage behavior of visitors. In the case of Gochang-gun, there was a phenomenon in which visitors were biased by region. This seems to be the result of Gochang-gun seeking to vitalize local tourism focusing on natural, ecological, and scenic resources. It is necessary to establish a plan for balanced regional development and develop other types of tourism resources. This study is different in that it identified the types and characteristics of rural tourism images in the region perceived by visitors, and the status of tourism at the regional level.

• International Journal of Contents
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• v.14 no.1
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• pp.1-6
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• 2018

Text, as one of the most influential inventions of humanity, has played an important role in human life since ancient times. The rich and precise information embodied in text is very useful in a wide range of vision-based applications such as the text data extracted from images that can provide information for automatic annotation, indexing, language translation, and the assistance systems for impaired persons. Therefore, natural-scene text detection with active research topics regarding computer vision and document analysis is very important. Previous methods have poor performances due to numerous false-positive and true-negative regions. In this paper, a fully-convolutional-network (FCN)-based method that uses supervised architecture is used to localize textual regions. The model was trained directly using images wherein pixel values were used as inputs and binary ground truth was used as label. The method was evaluated using ICDAR-2013 dataset and proved to be comparable to other feature-based methods. It could expedite research on text detection using deep-learning based approach in the future.

• International Journal of Contents
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• v.11 no.4
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• pp.77-85
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• 2015

Table detection is a challenging problem and plays an important role in document layout analysis. In this paper, we propose an effective method to identify the table region from document images. First, the regions of interest (ROIs) are recognized as the table candidates. In each ROI, we locate text components and extract text blocks. After that, we check all text blocks to determine if they are arranged horizontally or vertically and compare the height of each text block with the average height. If the text blocks satisfy a series of rules, the ROI is regarded as a table. Experiments on the ICDAR 2013 dataset show that the results obtained are very encouraging. This proves the effectiveness and superiority of our proposed method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.3
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• pp.194-202
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• 2003

To convert printed images into electronic ones automatically, it requires region analysis of document images and character recognition. In these, regional analysis segments document image into detailed regions and classifies thee regions into the types of text, picture, table and so on. But it is difficult to classify the text and the picture exactly, because the size, density and complexity of pixel distribution of some of these are similar. Thu, misclassification in region analysis is the main reason that makes automatic conversion difficult. In this paper, we propose region analysis method that segments document image into text and picture regions. The proposed method solves the referred problems using one dimensional median filter based method in text and picture classification. And the misclassification problems of boldface texts and picture regions like graphs or tables, caused by using median filtering, are solved by using of skin peeling filter and maximal text length. The performance, therefore, is better than previous methods containing commercial softwares.

• Journal of the Korea Convergence Society
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• v.8 no.8
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• pp.33-40
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• 2017

In this paper, we propose a text extraction method by pattern analysis on contour for effective text detection in image. Text extraction algorithms using edge based methods show good performance in images with simple backgrounds, The images of complex background has a poor performance shortcomings. The proposed method simplifies the color of the image by using K-means clustering in the preprocessing process to detect the character region in the image. Enhance the boundaries of the object through the High pass filter to improve the inaccuracy of the boundary of the object in the color simplification process. Then, by using the difference between the expansion and erosion of the morphology technique, the edges of the object is detected, and the character candidate region is discriminated by analyzing the pattern of the contour portion of the acquired region to remove the unnecessary region (picture, background). As a final result, we have shown that the characters included in the candidate character region are extracted by removing unnecessary regions.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.105-110
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• 2005

Painting and writing are exceedingly different in the way they are visually express. However, if one were to trace the roots of both painting and writing, one would discover the two have the same origins. At one time, both painting and writing fulfilled the function portraying mutual or reciprocal messages to the masses. On the other hand, after the time of medieval manuscript and typography, they were separated completely into image and text. Today, the images are interpreted into the text. Meanwhile, the text better communicates its ideas to the masses through additional support of the simultaneous image. The joint use of the shaping of mutual exchanges between literature and visual art is being enlivened between scholars through their tendency to converse or communicate through the media. Moreover, the visual configuration and characters that strike into the new media are one of the various uses and the significantly important methods of deliberative communication that are necessary for hypertext functioning. In the following text, I will expande and develope the historical communication scheme and the process of modification of painting and writing, lead the origination of modern new-pictograph.

• Bulletin of the Korean Space Science Society
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• 2000.10a
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• pp.110-110
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• 2000

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