• Fashion & Textile Research Journal
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• v.10 no.6
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• pp.811-821
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• 2008

This study examined on the most noticeable game industry in a digital era, and on the definition and feature of post-digital generation enjoying it, along with the relations with the game. Especially, this paper examined correlations between game characters' fashion and pop singers' fashion targeting post-digital generation enjoying games. As the result of this study, on-line game's popularity affected popular culture and game business and popular stars have close interrelation. In addition, through variosus objective surveys, the game characters' fashion was classified into five images before being analyzed; fighter's image, retro image, surreal image, sensual image, and unisexual image. The game characters' fashion wasn't only analyzed also studied correlation between on-line game character's fashion and pop singers' fashion by five images. Consequently in case of game characters' fashion, it influenced on pop singers' fashion targeting teens and twenties enjoying games, which meant fashion connections between game characters and pop singers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.10
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• pp.1877-1884
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• 2006

Image binarization is an important preprocessing to identify objects of interest by dividing pixels into background and objects. Usually binarization methods are classified into global and local thresholding approaches. In this paper, we propose an efficient and adaptive binarization method for the character segmentation by combining both advantages of the global and the local thresholding methods. Experimental results with the korean character images present that the proposed method binarizes character image faster and better than other local binarization methods.

• Proceedings of the Korea Society of Design Studies Conference
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• 2001.05a
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• pp.62-63
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• 2001

• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.481-490
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• 2002

Off-line handwritten character recognition is in difficulty of incomplete preprocessing because it has not dynamic information has various handwriting, extreme overlap of the consonant and vowel and many error image of stroke. Consequently off-line handwritten character recognition needs to study about preprocessing of various methods such as binarization and thinning. This paper considers running time of watershed algorithm and the quality of resulting image as preprocessing for off-line handwritten Korean character recognition. So it proposes application of effective watershed algorithm for segmentation of character region and background region in gray level character image and segmentation function for binarization by extracted watershed image. Besides it proposes thinning methods that effectively extracts skeleton through conditional test mask considering routing time and quality of skeleton, estimates efficiency of existing methods and this paper's methods as running time and quality. Average execution time on the previous method was 2.16 second and on this paper method was 1.72 second. We prove that this paper's method removed noise effectively with overlap stroke as compared with the previous method.

• Journal of Information Technology Applications and Management
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• v.29 no.4
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• pp.51-60
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• 2022

This study was conducted on characters who play the main character of the spin-off work based on the image in the original. Through the analysis of the original and spin-off works, the role type and characteristics according to the characters' roles were analyzed. It was analyzed that Rex, Bo Peep, and Forky, the main characters of the Toy Story spin-off works, had characteristics described in the original, which were not the main characters, and changed when they appeared in the spin-off works. First, it shows a tendency to add a new personality to play the role of the main character who solves problems and leads the story development while maintaining the existing personality characteristics in the original. Second, in order to play the main character in the spin-off work, these main characters are strongly revealed in the characteristics of the faithful type 6, and the achiever type 3, respectively. The reason why the characters' personality in the existing original have continuity is that if the personality of the existing characters change rapidly, they may contradict the audience's existing perception, preventing them from being immersed in the spin-off protagonist itself and the story development. However, the main characteristics of personality type 6 and personality type 3 are described only by considering the character's role as a helper to solve the problem and the characters' characteristics, but in order to solve the problem in spin-off, the animation producers are determined to achieve the goal. An understanding of this result will greatly help animation producers plan the character in consideration.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.525-533
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• 2003

In this paper we introduce some existing preprocessing algorithm for character recognition and consider feature extraction method for the recognition of low resolution document. Image recognition of low resolution document including fax images can be frequently misclassified due to the blurring effect, slope effect, noise and so on. In order to overcome these difficulties in the character recognition we considered a mesh feature extraction and contour direction code feature. System for automatic character recognition were suggested.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1081-1084
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• 1999

This paper proposes a method of extracting automobile license plate information using color image processing and separation of character regions. The hue and saturation of color information is need for license plate extraction and the specified standard location ratio is need for character region separation. Simulation results show that the proposed algorithm can detect license plates and separate character regions successfully.

• Journal of Digital Convergence
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• v.13 no.4
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• pp.319-328
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• 2015

Domestic kids TV animation industry is settled well in domestic animation industry by adding both entertainment value and educational value. Specially, the character that represents various rolls in the kids TV animation is the core visual element. This study is the analysis for character's subject matter of expression. For this, I established the tool which could classify character's subject matter of expression, and apply the tool to the character which were selected in broadcasting kids TV animations on EBS. Through this procedure, I analyzed character's subject matter of expression with the distribution chart as the final step. In addition, I hope the result of this study could intend to provide the index of the character creation in the kids TV animation and also informed the current situation about the character's subject matter of expression in the kids TV animation.

• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.31-36
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• 2017

In this paper, we try to search and reproduce the image part of a specific cast from a large number of images. The conventional method must manually set the offset value when searching for a scene or viewing a corner. However, in this paper, the proposed method learns the main character 's face, then finds the main character in the image recognition and moves to the scene where the main character appears to reproduce the image. Data for specific performers is extracted and collected using crawl techniques. Based on the collected data, we learn using convolutional neural network algorithm and perform performance evaluation using it. The performance evaluation measures the accuracy by extracting and judging a specific performer learned in the extracted key frame while playing the drama. The performance confirmation of how quickly and accurately the learned scene is searched has obtained about 93% accuracy. Based on the derived performance, it is applied to the image service such as viewing, searching for person and detailed information retrieval per corner

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.4
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• pp.15-24
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• 2007

The recognition of postal address images is indispensable for the automatic sorting of postal envelopes. The process of the address image recognition is composed of three steps-address image preprocessing, character recognition, address interpretation. The extracted character images from the preprocessing step are forwarded to the character recognition step, in which multiple candidate characters with reliability scores are obtained for each character image extracted. aracters with reliability scores are obtained for each character image extracted. Utilizing those character candidates with scores, we obtain the final valid address for the input envelope image through the address interpretation step. The envelope sorting rate depends on the performance of all three steps, among which character recognition step could be said to be very important. The good character recognizer would be the one which could produce valid candidates with very reliable scores to help the address interpretation step go easy. In this paper, we propose the method of generating character candidates with reliable recognition scores. We utilize the existing MLP(multilayered perceptrons) neural network of the address recognition system in the current automatic postal envelope sorters, as the classifier for the each image from the preprocessing step. The MLP is well known to be one of the best classifiers in terms of processing speed and recognition rate. The false alarm problem, however, might be occurred in recognition results, which made the address interpretation hard. To make address interpretation easy and improve the envelope sorting rate, we propose promising methods to reestimate the recognition score (confidence) of the existing MLP classifier: the generation method of the statistical recognition properties of the classifier and the method of the combination of the MLP and the subspace classifier which roles as a reestimator of the confidence. To confirm the superiority of the proposed method, we have used the character images of the real postal envelopes from the sorters in the post office. The experimental results show that the proposed method produces high reliability in terms of error and rejection for individual characters and non-characters.