• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.389-391
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• 2007

This paper describes about the printed character segmentation and recognition system for slabs in steel manufacturing process. To increase the recognition rate, it is important to improve success rate of character segmentation. Since Slabs front area surface are not uniform and surface temperature is very high, marked characters not only undergo damages but also have much noise. On the other hand, since almost marked characters are very thick and the space between characters is only about 10 $^{\sim}$ 15 mm, there are many touching characters. Therefore appropriate character image preprocessing and segmentation algorithm is needed. In this paper we propose a multi-local thresholding method for damaged character restoration, a modified touching character segmentation, algorithm for marked characters. Finally a effective Multi-Class SVM is used to recognize segmented characters.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.201-204
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• 1991

In this paper the method of representing the document image by the quadtree data structure, and extracting each character seperately from the constructed quadtree are described. The document image is represented by a binary encoded quadtree and the segmentation is performed according to the information of each leaf node of the quadtree. Then, each character is extracted by the relation of positions of segments. This method enables to extract characters without examining every pixel in the image and the required storage of document image is decreased.

• Journal of Korean Society of Rural Planning
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• v.15 no.2
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• pp.59-68
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• 2009

Nowadays, local governments have been developing an image to represent their regions' identity. These characters contain unlimited capabilities of utilization and advertising effect that adds to their high value. However, we must consider how effectively the image helps in representing its region because some characters have been produced upon timely basis without consistent long-term planning. This study is to investigate the image and motif of the local government characters from the consumer's perspective. The results are as follows: 1)The images employed by the local governments are not highly preferred and most regions select motifs from their local agricultural products and native plants. 2)The variables that affect the character of the local governments are such as beauty, identity, etc. In conclusion, in order to maximize the local government image, one must improve the design concepts, encourage advertisement of regional festivities and travel commercialization, and advocate the identity and beauty of the local area to the residents and other regional people.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.6
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• pp.61-69
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• 1994

For distortion-invariant recognition of Korean characters, a holographic implementation of an optical associative memory system is proposed. The structure of the proposed system is a single-layer neural network employing interconneclion matrix, thresholding and feedback. To provide the interconnection matrix, we use two CGII's which are placed on intermcdiate plane of cascaded Vander Lugt corrclators to form an optical memory loop. The holographic correlator stores reference images in a hologram and retrives them in a coherently illuminated feedback loop. An input image which maybe noisy or incomplete, is applicd to the system and simultaneously correlated optically with all of the stord images. These correlations are throsholed and fed back to the input, where the strongest correlation reinforces the input image. The enhanced image passes arround the loop repeatedly, approaching the stored image more closely on each pass until the system stabilizes on the desired image. The computer simulation results show that the proposed Korean Character recognition algorithm has high discrimination capability and noise immunity.

• Journal of the Korean Society of Costume
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• v.59 no.1
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• pp.1-13
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• 2009

The villains in recent films are given interesting roles not only through the actual contents of the story but also by attractive personal characteristics including internal and psychological aspects. The purpose of this paper is to take a deeper look into the image styling process of villain characters. The cases will focus on seven representative Korean films that have attracted over one million audiences as of the year 2000, and the leading and supporting actors within those films. Analysis will be made mainly on the visual image creations of those villains. The visual images are categorized by the make-up, hair-do, clothing and accessories relevant to the psychological personality type of each actor's role and their background based on the given scenarios. The results are as follows: First, villain characters are portrayed as an individual with multiple personalities with regards to psychological, economical, and vocational aspects. Second, fashion trends of the character is an important element to keep pace with the times or to visualize the sense of the times in which the villain exists. Third, a specific point that characterizes the villain's character are expressed through various touches using noticeable accessories, specific colors in make up, hair style, and a certain fashion.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.2
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• pp.180-195
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• 1991

In this paper, we studied on new method of recognition using structural information to recognize character pattern in orginal shape of Hangeul. First, for the purpose of knowing location of character in input image. it processed Making block. Second, after we investigated. whether vertical vowel exited or not in character image accordingly the center of gravity of Hangeul. each character was classified into Type of Hangeul by searching location and length for horizontal vowel and short pole. Last, we processed it by means of template matching which calculate Uclid's distance on each Jaso in accordance to type classified. This paper made an experiment on 2350 characters and obtained 98.3% classifing rate and 95.2% recognizing rate.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.209-215
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• 2017

Character of emoticon is considered suitable for expressivity in the digital era mixing and using contents of conversation with images in the course of having a talk with the other party in the mobile space. For the foregoing, this study carried out multiple regression analysis having factors of character attribute such as awareness, friendliness, self-expressivity and image differentiation as independent variables, and purchase intention of purchasers as a dependent variable. Analysis results show that awareness and image differentiation had a positive influence on the purchase intention, whereas friendliness and self-expressivity exerted no significant influence on the purchase intention.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.451-455
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• 2008

In this paper we embody a system that recognizes the printed alphabet of two font types (Batang, Dodum) inputted by a black-and-white CCD camera and converts it into an editable text form. The image of the inputted printed sentences is binarized, then the rows of each sentence are separated through the vertical projection using the Histogram method, and the height of the characters are normalized to 48 pixels. With the reverse application of the basic principle of the Nonogram puzzle to the individual normalized character, the character is covered with the pixel-based squares, representing the characteristics of the character as the numerical information of the Nonogram puzzle in order to recognize the character through the comparison with the standard pattern information. The test of 2609 characters of font type Batang and 1475 characters of font type Dodum yielded a 100% recognition rate.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.73-78
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• 2006

Conventional caption extraction methods use the difference between frames or color segmentation methods from the whole image. Because these methods depend heavily on heuristics, we should have a priori knowledge of the captions to be extracted. Also they are difficult to implement. In this paper, we propose a method that uses little heuristic and simplified algorithm. We use topographical features of characters to extract the character points and use MST(Minimum Spanning Tree) to extract the candidate regions for captions. Character regions are determined by testing several conditions and verifying those candidate regions. Experimental results show that the candidate region extraction rate is 100%, and the character region extraction rate is 98.2%. And then we can see the results that caption area in complex images is well extracted.

• The Research Journal of the Costume Culture
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• v.29 no.4
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• pp.603-615
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• 2021

The aim of this study was to analyze the semantic network structure of keywords and the visual composition of images extracted from Instagram in relation to the multi-persona phenomenon with in fashion imagery, which has recently been attracting attention. To this end, the concept of a 'secondary character', which forms a separate identity from a 'main character' on various social media platforms as well as on the airwaves, was considered as the spread of multi-persona and #SecondaryCharacter on Instagram was investigated. 3,801 keywords were collected after crawling the data using Python and morphological analysis was undertaken using KoNLP. The semantic network structure was then examined by conducting a CONCOR analysis using UCINET and Netdraw to determine the top 50 keywords. The results were then classified into a total of 6 clusters. In accordance with the meaning and context of the keywords included in each cluster, group names were assigned : virtual characters, relationship with the main character, hobbies, daily record, N-job person, media and marketing. Image analysis considered the technical, compositional, and social styles of the media based on Gillian Rose's visual analysis method. The results determined that Instagram uses fashion images that virtualize one's face to produce multi-persona representation s that show various occupations, describe different types of hobbies, and depict situations pertaining to various social roles.