• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.31-34
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• 2003

In this paper, we describe a method for separating text lines in handwritten Korean address images. The most remarkable feature of the proposed method is to use a modified projection technique. named a partial projection technique. A projection based text line separation method which projects the whole address image in horizontal direction to find split points for text line separation cannot avoid failing separation in case of images with a little skew or overlap between vertically neighboring text lines. To overcome this problem, we have introduced a partial projection technique which splits an address image into a few partial address images to be equal width and then project them each horizontally. The experiment done with 989 handwritten Korean address images extracted from live mails shows the superiority of the proposed method. The correct text-line separation rate fir the testing images was about 91.5％.

• The Research Journal of the Costume Culture
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• v.28 no.1
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• pp.15-29
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• 2020

Purpose of the study is to explore the effect of the types of mobile coupons(text- vs. image-focused coupons; free-gift vs. discount coupons) on characteristic perception of mobile coupons, and the causal relationships among characteristic perception, attitude, and use intention of mobile coupons. A total of 140 university students participated in experiments with questionnaires including one of the four stimuli. Important findings are as follows. First, image-focused mobile coupons generated more enjoyment than did text-focused coupons. However, the text/image-focused coupons were not different in perception of informativeness and credibility of mobile coupons. Second, enjoyment perception was significantly increased when image-focused contents were combined with discount coupons whereas enjoyment perception was decreased when text-focused contents were combined with free-gift coupons. This interaction effect reflects that the level of enjoyment of consumers can be changed in terms of the combination of the value-provision types of coupons and the text-image focused contents. Third, it was found that consumer perception of coupon characteristics formed attitudes toward mobile coupons, and use intention of mobile coupons was determined by attitudes toward mobile coupons. Study findings may fill the void of research investigating the effect of text-image contents and the types of coupons on consumer reponses toward mobile coupons. Mobile coupons have limited quantity of information within a small size of mobile phone screen, therefore, the results were not consistent with prior research tested with mobile advertisements indicating the effect of text-image contents on perception of informativeness and credibility.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.1025-1034
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• 2009

In steel making production line, steel slabs are given a unique identification number. This identification number, Slab management number(SMN), gives information about the use of the slab. Identification of SMN has been done by humans for several years, but this is expensive and not accurate and it has been a heavy burden on the workers. Consequently, to improve efficiency, automatic recognition system is desirable. Generally, a recognition system consists of text localization, text extraction, character segmentation, and character recognition. For exact SMN identification, all the stage of the recognition system must be successful. In particular, the text localization is great important stage and difficult to process. However, because of many text-like patterns in a complex background and high fuzziness between the slab and background, directly extracting text region is difficult to process. If the slab region including SMN can be detected precisely, text localization algorithm will be able to be developed on the more simple method and the processing time of the overall recognition system will be reduced. This paper describes about the slab region localization using SIFT(Scale Invariant Feature Transform) features in the image. First, SIFT algorithm is applied the captured background and slab image, then features of two images are matched by Nearest Neighbor(NN) algorithm. However, correct matching rate can be low when two images are matched. Thus, to remove incorrect match between the features of two images, geometric locations of the matched two feature points are used. Finally, search rectangle method is performed in correct matching features, and then the top boundary and side boundaries of the slab region are determined. For this processes, we can reduce search region for extraction of SMN from the slab image. Most cases, to extract text region, search region is heuristically fixed [1][2]. However, the proposed algorithm is more analytic than other algorithms, because the search region is not fixed and the slab region is searched in the whole image. Experimental results show that the proposed algorithm has a good performance.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.196-202
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• 1999

Recent trend changes a criterion for evaluation of burner that environmental problem is raised as global issue. For efficient driving problem, the higher thermal efficiency and the lower oxygen in exhaust gas, burner is evaluated the better. For environmental problem, burner must satisfy $NO_{X}$ limit and CO limit. Consequently, 'good burner' means on whose thermal efficiency is high under the constraint of $NO_{X}$ and CO consistency. To make existing burner satisfy recent criterion, it is highly recommended to develop feedback control scheme whose output is the consistency of $NO_{X}$ and CO. This paper describes development of real time flame diagnosis technique that evaluate and diagnose combustion state such as consistency of components in exhaust gas, stability of flame in quantitative sense. This study focuses on wave length of luminescence from chemical reaction measurement of the luminescence via optical measuring apparatus and derive correlation with consistency of components in exhaust gas by image processing technique.

• Current Optics and Photonics
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• v.3 no.4
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• pp.320-328
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• 2019

A method for joint-transform correlator (JTC) multiple-image encryption based on a quick-response (QR) code key is proposed. The QR codes converted from different texts are used as key masks to encrypt and decrypt multiple images. Not only can Chinese text and English text be used as key text, but also symbols can be used. With this method, users have no need to transmit the whole key mask; they only need to transmit the text that is used to generate the key. The correlation coefficient is introduced to evaluate the decryption performance of our proposed cryptosystem, and we explore the sensitivity of the key mask and the capability for multiple-image encryption. Robustness analysis is also conducted in this paper. Computer simulations and experimental results verify the correctness of this method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.32-37
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• 2009

Recently, electronic mail(E-mail) is the most popular communication manner in our society. In such conventional environments, spam increasingly congested in Internet. In this paper, Chinese spam could be effectively detected using text and image features. Using text features, keywords and reference templates in Chinese mails are automatically selected using genetic algorithm(GA). In addition, spam containing a promotion image is also filtered out by detecting the text characters in images. Some experimental results are given to show the effectiveness of our proposed method.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.505-506
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• 2022

인공지능 기술은 점차 빠른 속도로 발전되며 응용 분야가 확대되어 창작 산업에서의 역할도 커져 예술, 영화 및 기타 창조적인 산업에도 영향을 주고 있다. 이러한 인공지능 기술을 이용하여 텍스트로 설명하면 다양한 스타일의 이미지를 생성해내는 기술이 있지만 아동이 직접 그린 손그림 스타일의 그림을 생성하지는 못한다. 본 논문에서는 아동 손그림 데이터를 통해 Text-to-Image를 학습시켜 새로운 학습 모델을 생성하는 과정에 대해서 기술한다. 이 연구를 통해 생성된 픽셀을 결합하여 텍스트를 기반으로 하나의 아동 손그림을 만들 수 있을 것으로 기대한다.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.5
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• pp.789-809
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• 2020

Growth in online channels has created fierce competition; consequently, retailers have to invest an increasing amount of effort into attracting consumers. In this study, eye-tracking technology examined consumers' visual behavior to gain an understanding of information searching behavior in exploring product information for fashion products. Product attribute information was classified into two image-based elements (model image information and detail image information) and two text-based elements (basic text information, detail text information), after which consumers' visual behavior for each information element was analyzed. Furthermore, whether involvement affects consumers' information search behavior was investigated. The results demonstrated that model image information attracted visual attention the quickest, while detail text information and model image information received the most visual attention. Additionally, high-involvement consumers tended to pay more attention to detailed information while low-involvement consumers tended to pay more attention to image-based and basic information. This study is expected to help broaden the understanding of consumer behavior and provide implications for establishing strategies on how to efficiently organize product information for online fashion stores.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1111-1120
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• 2022

Image Capturing is a matter of viewing images and describing images in language. The problem is an important problem that can be solved by keeping, understanding, and bringing together two areas of image processing and natural language processing. In addition, by automatically recognizing and describing images in text, images can be converted into text and then into speech for visually impaired people to help them understand their surroundings, and important issues such as image search, art therapy, sports commentary, and real-time traffic information commentary. So far, the image captioning research approach focuses solely on recognizing and texturing images. However, various environments in reality must be considered for practical use, as well as being able to provide image descriptions for the intended purpose. In this work, we limit the universally available Korean and English image captioning models and text generation techniques for the purpose of image captioning.