• The KIPS Transactions:PartB
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• v.14B no.6
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• pp.453-460
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• 2007

In this paper, we present a method to extract the text lines in poorly structured documents. The text lines may have different orientations, considerably curved shapes, and there are possibly a few wide inter-word gaps in a text line. Those text lines can be found in posters, blocks of addresses, artistic documents. Our method based on the traditional perceptual grouping but we develop novel solutions to overcome the problems of insufficient seed points and vaned orientations un a single line. In this paper, we assume that text lines contained tone connected components, in which each connected components is a set of black pixels within a letter, or some touched letters. In our scheme, the connected components closer than an iteratively incremented threshold will make together a chain. Elongate chains are identified as the seed chains of lines. Then the seed chains are extended to the left and the right regarding the local orientations. The local orientations will be reevaluated at each side of the chains when it is extended. By this process, all text lines are finally constructed. The proposed method is good for extraction of the considerably curved text lines from logos and slogans in our experiment; 98% and 94% for the straight-line extraction and the curved-line extraction, respectively.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.5
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• pp.310-318
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• 2016

Emerging technologies such as the Internet of Things (IoT) and the Advanced Driver Assistant System (ADAS) often have image transmission functions with tough constraints, like low power and/or low delay, which require that they adopt line-based, low memory compression methods instead of existing frame-based image compression standards. Bit rate control in the conventional frame-based compression systems requires a lot of hardware resources when the scope of handled data falls at the frame level. On the other hand, attempts to reduce the heavy hardware resource requirement by focusing on line-level processing yield uneven image quality through the frame. In this paper, we propose a bit rate control that maintains consistency in image quality through the frame and improves the legibility of text regions. To find the line characteristics, the proposed bit rate control tests each line for ease of compression and the existence of text. Experiments on the proposed bit rate control show peak signal-to-noise ratios (PSNRs) similar to those of conventional bit rate controls, but with the use of significantly fewer hardware resources.

• Bulletin of the Korean Space Science Society
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• 1998.10a
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• pp.53.2-53
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• 1998

No Abstract.See Full-text

• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.912-919
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• 2009

A novel algorithm using 2D tensor voting and edge-based approach is proposed for text detection in natural scene images. The tensor voting is used based on the fact that characters in a text line are usually close together on a smooth curve and therefore the tokens corresponding to centers of these characters have high curve saliency values. First, a suitable edge-based method is used to find all possible text regions. Since the false positive rate of text detection result generated from the edge-based method is high, 2D tensor voting is applied to remove false positives and find only text regions. The experimental results show that our method successfully detects text regions in many complex natural scene images.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.251-252
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• 2007

The thesis proposed the Text Extraction Algorithm which is a text extraction algorithm which uses the Coiflet Wavelet, YCbCr Color model and the close curve edge feature of adaptive LoG Operator in order to complement the demerit of the existing research which is weak in complexity of background, variety of light and disordered line and similarity of text and background color. This thesis is simulated with natural images which include naturally text area regardless of size, resolution and slant and so on of image. And the proposed algorithm is confirmed to an excellent by compared with an existing extraction algorithm in same image.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.2
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• pp.153-166
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• 2015

This paper proposes a trans-media branding for the trans-media-based cultural content marketing strategy. Trans-media brand analytical framework is proposed with previous studies. And mobile messenger Character 'Line Friends' is analyzed for the text. Trans-media branding is accessible through a multi-platform in the technological environment. Consumer culture, as well as participate include business models to generate revenue also as brand equity. While the character elements that make up the story from the perspective of cultural content storytelling act as an independent cultural goods. Character is segmented elements. Therefore, trans- media branding of the characters are more meaningful. 'Line Friends' trans-media branding can be summarized as follows: First, it takes advantage of the characteristics of the existing Information-Technology-based mobile. Second, it puts consistently found the content of the attributes of Mobile Messenger 'communication' and 'friendship'. And third, while the content of each platform is constantly linked with other platforms, the brand is positioned inside the window effect.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.373-376
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• 2002

This paper represents a survey of a variety thresholding techniques including both global and local thresholding. Several thresholding methods are examined in detail to evaluate their performance based on a given set of test images. We also attempt to evaluate the performance of several thresholding methods for construction field documents image recognition system using a broken line structures, broken symbols and text, blurring of lines, symbols and text, noise in homogeneous areas measure as a criterion functions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.531-534
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• 2005

Currently some problems are presented by the enlargement of network range and hardware upgrade for the solutions for network traffic and treatment speed of server processing, as well as the resource of networks and increasing speed of on-line information that is exceeding in operation limit of existing information systems. The study proposes the Architecture, an organic unification system of optimized content for retrieval, which is adapted to variable points of view of users or content changes of document aggregation by the study of algorithm, which offers easy retrieval of the location of documents on a multitude of on-line data.

• Journal of radiological science and technology
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• v.45 no.6
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• pp.543-552
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• 2022

This study compared and analyzed with the United States(USA) to evaluated the level of readability of radiotherapy information (English text) provide to foreign patients with cancer by medical institutions in South Korea (KOR). A total of 20 the KOR and USA medical hospitals in 10 each provide information for radiation therapy technology were selected. The readability was comparatively analyzed a total of three aspects (lexical, syntactic, cohesion and readability) by using a Coh-Metrix on-line web program. In readability respect, the mean of the Flesch Reading Ease (FRE) was lower in the KOR (8.3) than in the USA (23.2), Flesch-Kincaid grade level (FKGL) was higher in the KOR than in the USA (14.2) indicating that KOR was less readable than the US (p<.05). In both KOR and USA, the reading level (literacy) of the English text for the radiation therapy was found to be higher than high school (FRE level 50 or lower). Therefore, text information in English for the radiation therapy to foreign patients with cancer should be lowered to elementary school level and read to improve the quality of medical services.

• Journal of Computing Science and Engineering
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• v.5 no.3
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• pp.161-166
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• 2011

We present a fast algorithm for Korean text extraction and segmentation from subway signboards using smart phone sensors in order to minimize computational time and memory usage. The algorithm can be used as preprocessing steps for optical character recognition (OCR): binarization, text location, and segmentation. An image of a signboard captured by smart phone camera while holding smart phone by an arbitrary angle is rotated by the detected angle, as if the image was taken by holding a smart phone horizontally. Binarization is only performed once on the subset of connected components instead of the whole image area, resulting in a large reduction in computational time. Text location is guided by user's marker-line placed over the region of interest in binarized image via smart phone touch screen. Then, text segmentation utilizes the data of connected components received in the binarization step, and cuts the string into individual images for designated characters. The resulting data could be used as OCR input, hence solving the most difficult part of OCR on text area included in natural scene images. The experimental results showed that the binarization algorithm of our method is 3.5 and 3.7 times faster than Niblack and Sauvola adaptive-thresholding algorithms, respectively. In addition, our method achieved better quality than other methods.