• Journal of Korea Multimedia Society
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• v.17 no.9
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• pp.1125-1133
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• 2014

Recently, there are many researches have been studying for analyzing user interests and emotions based on users profiles and diverse information from Social Network Services (SNSs) due to their popularities. However, most of traditional researches are focusing on their researches based on single resource such as text, image, hash tag, and more, in order to obtain what user emotions are. Hence, this paper propose a method for obtaining user emotional information by analyzing texts and images both from Instagram which is one of the well-known image based SNSs. In order to extract emotional information from given images, we firstly apply GRAB-CUT algorithm to retrieve objects from given images. These retrieved objects will be regenerated by their representative colors, and compared with emotional vocabulary table for extracting which vocabularies are the most appropriate for the given images. Afterward, we will extract emotional vocabularies from text information in the comments for the given images, based on frequencies of adjective words. Finally, we will measure WUP similarities between adjective words and emotional words which extracted from the previous step. We believe that it is possible to obtain more precise user emotional information if we analyzed images and texts both time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2390-2406
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• 2022

Scene text recognition has important application value and attracted the interest of plenty of researchers. At present, many methods have achieved good results, but most of the existing approaches attempt to improve the performance of scene text recognition from the image level. They have a good effect on reading regular scene texts. However, there are still many obstacles to recognizing text on low-quality images such as curved, occlusion, and blur. This exacerbates the difficulty of feature extraction because the image quality is uneven. In addition, the results of model testing are highly dependent on training data, so there is still room for improvement in scene text recognition methods. In this work, we present a natural scene text recognizer to improve the recognition performance from the feature level, which contains feature representation and feature enhancement. In terms of feature representation, we propose an efficient feature extractor combined with Representative Batch Normalization and ResNet. It reduces the dependence of the model on training data and improves the feature representation ability of different instances. In terms of feature enhancement, we use a feature enhancement network to expand the receptive field of feature maps, so that feature maps contain rich feature information. Enhanced feature representation capability helps to improve the recognition performance of the model. We conducted experiments on 7 benchmarks, which shows that this method is highly competitive in recognizing both regular and irregular texts. The method achieved top1 recognition accuracy on four benchmarks of IC03, IC13, IC15, and SVTP.

• Journal of Information Technology Services
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• v.15 no.3
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• pp.147-155
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• 2016

According to rapid development of technology, web text is growing explosively and attracting many fields as substitution for survey. The user of Facebook is reaching up to 113 million people per month, Twitter is used in various institution or company as a behavioral analysis tool. However, many research has focused on meaning of the text itself. And there is a lack of study for text's creation subject. Therefore, this research consists of sex/age text classification with by using 20,187 Facebook users' posts that reveal the sex and age of the writer. This research utilized Convolution Neural Networks, a type of deep learning algorithms which came into the spotlight as a recent image classifier in web text analyzing. The following result assured with 92% of accuracy for possibility as a text classifier. Also, this research was minimizing the Korean morpheme analysis and it was conducted using a Korean web text to Authorship Attribution. Based on these feature, this study can develop users' multiple capacity such as web text management information resource for worker, non-grammatical analyzing system for researchers. Thus, this study proposes a new method for web text analysis.

• 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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• 2001.06c
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• pp.5-8
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• 2001

The computer programs based upon graphic user interface(GUI) became commonplace with the advance of computer technology. Nevertheless, programs for the visually-handicapped have still remained at the level of TTS(text to speech) programs and this prevents many visually-handicapped from enjoying the pleasure and convenience of the information age. This paper is, paying attention to the importance of character recognition in images, about the configuration of the system that converts text in the image selected by a user to the speech by extracting the character part, and carrying out character recognition.

• The Research Journal of the Costume Culture
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• v.11 no.1
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• pp.135-152
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• 2003

The purpose of this study is to analyze the symbolic meaning which is immanent in the children´s clothing advertisement text. For the purpose of this research, this study used the semiotic method which are in parallel. Namely, rearranged the R. Barthes´theory and S. Chapman's analysing frame in order to decode meaning which is immanent in the advertisement text, and 1 coded children's clothing advertisement according to the market fractionation cause (age. sex and brand image), and analysed the paradigmatic meaning and socio-cultural meaning- As a result, to carry on the effective children's clothing advertisements. the discriminate paradigmatic system which corresponds with the concept of company brand and the quality of the target consumer should be selected, and the purchaser volition considering desire of target consumer's self image and brand image should be made. Futhermore it should be the social-cultural product reflecting a phenomenon in the social-cultural actual condition. Therefore we must understand the social-cultural meaning in the children's clothing advertisement and then have to establish an advertisement strategy.

• International Journal of Contents
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• v.9 no.1
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• pp.1-5
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• 2013

Standard Gaussian Mixture Model (GMM) is a well-known method for image segmentation. However, one of its problems is that we consider the pixel as independent to each other, which can cause the segmentation results sensitive to noise. It explains why some of existing algorithms still cannot segment texts from the background clearly. Therefore, we present a new method in which we incorporate the spatial relationship between a pixel and its neighbors inside $3{\times}3$ windows to segment the text. Our approach works well with images containing texts, which has different sizes, shapes or colors in case of light changes or complex background. Experimental results demonstrate the robustness, accuracy and effectiveness of the proposed model in image segmentation compared to other methods.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.554-559
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• 1999

The purpose of this study is the machining of texture shapes by the contour fitting data. The hardware of the system comprises PC and scanning system, CO2 laser machine. There are four steps, (1) text image loading using scanning shapes or 2D image files, (2) generation of contour fitting data by the line and arc, cubic Bezier curve, (3) generation of NC code from the contouring fitting data, (4) machining by the DNC system. It is developed a software package, with which can conduct a micro CAM system of CNC laser machine in the PC without economical burden.

• Journal of the Korean Society for information Management
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• v.9 no.1
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• pp.131-164
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• 1992

In this study. a technical report management system using optical technology is described in detail. This management system is designed for both bibliographic (character) and full-text (image) information. Several optical filing systems already on the Korean market are scrutinized and compared with standard functions in order to build a more efficient management system for technical reports which can be easily integrated into existing KRISS library automation system. For that purpose, up-to-date technologies (i.e., digital image PI-ocessing (DIP), MARC standards, and optical character recognition (OCR), etc.) are applied to this system.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.285-291
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• 2022

With the growing exchange of data between individuals and institutions through various electronic communication, valuable data protection is in high demand to ensure that it is not hacked and that privacy is protected. Many security techniques, such as encryption and steganography, have emerged to prevent security breaches. The purpose of this research is to integrate cryptographic and steganography techniques to secure text message sending. The Rijndael algorithm was used to encrypt the text message, and the Least Significant Bit algorithm was also used to hide the encrypted message in a color image. Experiments on the suggested method have proven that it can improve the security of sent messages due to the human eye's inability to identify the original image from the image after it has been covered, as well as the encryption of the message using a password.