• Journal of Korea Multimedia Society
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• v.14 no.6
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• pp.813-823
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• 2011

This study is to suggest the facial animation methodology for that 3D character animators can use CGS system effectively during on their stage which they create ideas and use repeating a process of facial animation, it has suggested the CGS(Character Generation System) that is a creative idea generation methodology identified and complemented the problem of the existing computerized idea generation, in addition, this research being extended on the article vol.13, no.7, "CGS System based on Three-Dimensional Character Modeling II (Part2: About Digital Process)," on Korea Multimedia Society in July 2010 issue, Through the preceding study on 3D character facial expression according to character's feelings as an anatomical structure and the case study on character expressions of theatrical animation, this study is expected to have effectives as one method for maximization of facial animation and idea generation ability.

• Proceedings of the Korea Society of Design Studies Conference
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• 2001.05a
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• pp.36-37
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• 2001

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.2
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• pp.121-125
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• 2015

In this paper, we propose a method that extracts features from character patterns using the fractal dimension of chaos theory. The input character pattern image is converted into time-series data. Then, using the modified Henon system suggested in this paper, it determines the last features of the character pattern image after calculating the box-counting dimension, natural measure, information bit, and information (fractal) dimension. Finally, character pattern recognition is performed by statistically finding each information bit that shows the minimum difference compared with a normalized character pattern database.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.9
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• pp.14-22
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• 2015

TIn this paper, a centering method for an unfocused input character using the spherical domain system and the centering character to use the shift invariant feature for the recognition system is proposed. A system for recognition is implemented using the centroid method with coordinate average values, and the results of an above 78.14% average differential ratio for the character features were obtained. It is possible to extract the shift invariant feature using spherical transformation similar to the human eyeball. The proposed method, which is feature extraction using spherical coordinate transform and transformed extracted data, makes it possible to move the character to the center position of the input plane. Both digital and optical technologies are mixed using a spherical coordinate similar to the 3 dimensional human eyeball for the 2 dimensional plane format. In this paper, a centering character feature using the spherical domain is proposed for character recognition, and possibilities for the recognized possible character shape as well as calculating the differential ratio of the centered character using a centroid method are suggested.

• Journal of Intelligence and Information Systems
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• v.10 no.3
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• pp.1-10
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• 2004

In this paper, a new character segmentation algorithm of machine printed character recognition is proposed. The new approach of the proposed character segmentation algorithm overcomes the weak points of both feature-based approaches and recognition-based approaches in character segmentation. This paper defines side profiles of touching characters. The character segmentation algorithm gives a candidate single character in touching characters by side profiles, without any help of character recognizer. It segments touching characters and decides the candidate single character by side profiles. This paper also defines cutting cost, which makes the proposed character segmentation find an optimal segmenting path. The performance of the proposed character segmentation algorithm in this paper has been obtained using a real envelope reader system, which can recognize addresses in U.S. mail pieces and sort the mail pieces. 3359 mail pieces were tested. The improvement was from $68.92\%\;to\;80.08\%$ by the proposed character segmentation.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.3
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• pp.241-247
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• 2006

We propose a character recognition system to extract the component reference names from printed circuit boards (PCBs) automatically. The names are written in horizontal, vertical, reverse-horizontal and reverse-vertical directions. Also various symbols and figures are included in PCBs. To recognize the character and orientation effectively, we divide the recognizer into two stages: character classification stage and orientation classification stage. The character classification stage consists of two sub-recognizers and a verifier. The rotaion-invarint features of input pattern are then used to identify the character independent of orientation. Each recognizer is implemented as a neural network, and the weight values of verifier are obtained by genetic algorithm. In the orientation classification stage, the input pattern is compared with reference patterns to identify the orientation. Experimental results are presented to verify the usefulness of the proposed system.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.302-306
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• 1994

This paper describes how to recognize hand written Hangeul character using the stroke order of the elementary segment. The recognition system is constructed of parts : character input part, segment disassembling part, character element extraction part and character recognition part. The character input part reads the character and performs thinning algorithm. In the segment disassembling part, the input character is disassembled into elementary segments using the direction codes and the feature parameters. In the character element extraction part, we extract the character element using the stroke order and the knowledge rule. Finally, we able to recognize the hand written Hangeul characters by assembling the character elements, in the character recognition part.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2004.11a
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• pp.237-240
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• 2004

This paper describes a character retrieval system for TV programs and a set of novel algorithms for detecting and recognizing faces for the system. Our character retrieval system consists of two main components: Face Register and Face Recognizer. The Face Register detects faces in video frames and then guides users to register the detected faces of interest into the database. The Face Recognizer displays the appearance interval of each character on the timeline interface and the list of scenes with the names of characters that appear on each scene. These two components also provide a function to modify incorrect results. which is helpful to provide accurate character retrieval services. In the proposed face detection and recognition algorithms. we reduce the computation time without sacrificing the recognition accuracy by using the DCT/LDA method for face feature extraction. We also develop the character retrieval system in the form of plug-in. By plugging in our system to a cataloguing system. the metadata about the characters in a video can be automatically generated. Through this system, we can easily realize sophisticated on-demand video services which provide the search of scenes of a specific TV star.

• ETRI Journal
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• v.39 no.2
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• pp.163-172
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• 2017

A high performance license plate recognition system (LPRS) is proposed in this work. The proposed LPRS is composed of the following three main stages: (i) plate region determination, (ii) character segmentation, and (iii) character recognition. During the plate region determination stage, the image is enhanced by image processing algorithms to increase system performance. The rectangular license plate region is obtained using edge-based image processing methods on the binarized image. With the help of skew correction, the plate region is prepared for the character segmentation stage. Characters are separated from each other using vertical projections on the plate region. Segmented characters are prepared for the character recognition stage by a thinning process. At the character recognition stage, a three-layer feedforward artificial neural network using a backpropagation learning algorithm is constructed and the characters are determined.

• International journal of advanced smart convergence
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• v.7 no.3
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• pp.130-139
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• 2018

This study is to analyze the relationship between character and human semantic production through research on character visualization artworks and to develop a creative platform that visually expresses the formative and semantic dynamics of characters using the results will be. The 3D spatial interaction system using the character visualization proposed generates the transformation of the character in real time using the interaction with user and the deconstruction of the character structure. Transformations of characters including the intentions of the viewers provide a dynamic visual representation to the viewer and maximize the efficiency of meaning transfer by producing various related meanings. The method of dynamic deconstruction and reconstruction of the characters provided by this system creates special shapes that viewers cannot imagine until now and further extends the interpretation range of the meaning of the characters. Therefore, the proposed system not only induces an active viewing attitude from viewers, but also gives them an opportunity to enjoy watching the artwork and demonstrate creativity as a creator. This system induces new gestures of the viewer in real time through the transformation of characters in accordance with the viewer''s gesture, and has the feature of exchanging emotions with viewers.