• The Journal of the Korea Contents Association
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• v.11 no.6
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• pp.67-75
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• 2011

We propose a novel non-photorealistic rendering technique which generates a cutout animation from a video for UCC. Our method consists of four parts. First, we construct an interactive system to build an articulated character. Second, we extract motions from an input video. Third, we transform motions of a character in order to reflect characteristics of cutout animations. Fourth, we render the extracted or transformed components in cutout animation style. We developed a unified system for a user to easily create a cutout animation from an input video and showed the system generated a cutout animation efficiently.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.9
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• pp.1269-1282
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• 1993

In this paper, we propose to method of recognizing printed chinese characters which combine the coventional deterministic methods and the neural networks. Firstly, we extract four directional vector of strokes from chinese characters. Secondly, we make the mesh of the center of gravity in the vector and then constitute the H x8 feature matrix using black pixel lenth from each meshs. This normalized feature matrix value offer as the input of neural network for classifying into the 14 character types. And this calssified character classify again into Busu group by the Busu recognizing neural network. Finally, we recognize each characters using the distance of similarity between input characters and reference characters. The usefulness of the proposed algorithm is evaluated by experimenting with recognizing the chinese characters.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.6
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• pp.76-85
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• 1993

In this paper, we propose a stroke matching method for the off-line recognition of handprinted Hangul. In this method, the preprocessing steps such as position normalization, contour tracing and thinning are carried out first. Then, after extracting features such as the firection component distribution of contour, the direction component distribution of skeleton, and the distribution of structural feature points, strokes are extracted and matched based on the midpont distribution of the direction and the length of each stroke. In order to reduce the recognition time, a preliminary classification based on the direction component distribution features of the contour is performed. In order to domonstrate the performance of the proposed method, experiments with 520 most frequently used Hangul were performed, and 90.7% of correct recognition rate and 0.46second of recognition time per one character has been obtained. This results reveal that the proposed method can absorb effectively the noise in input character and the variations of stroke slant.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11
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• pp.3584-3591
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• 2000

In this paper we propose measure for performance evaluationof character recognition, We used three commercial character recognizers and one laboratory character recognizer for test. The characteristics of each recognizer is compared by proposed evaluation standrd, and analyzed characteristrics For the input test data, KT test collection are used. KT test collection is composed of 1000 document images about and complete source text. In this paper we propose method for measuring recognition rage in character unit for evaluation of character recogrition, The recogrition rates are compared and analyzed by single feature characteristic or mixed feature characteristic.

• Journal of Korea Multimedia Society
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• v.9 no.4
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• pp.414-420
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• 2006

Online character recognition techniques have been applied in many new fields of PDA, Tablet PC etc. But the recognition techniques can not use such high technologies naturally yet. Hidden Markov Model (HMM) that is much used recently requires high memory space and complex computational tasks because of comparing the input data with entire standard patterns. In this paper we propose a method to recognize the online characters more efficiently. At first we create chain-codes of learning data and recognition data in preprocessing phase, and then we compress dimensions of data using Principal Component Analysis (PCA) and recognize a character compressed data in recognition phrase. Validity of proposed method .is verified. by experiment results.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1873-1880
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• 1997

It is an important factor to distinguish the kind of the character for increasing recognition rate before the character recognition in the document recognition system composed of the multi-font and multi-letters. All the letters of each country have a various unique characteristic in the each composition. In this paper, we used the stroke density as a method to distinguish the letter, and it has been adopted only Korean and English character. Input data is processed by the normalization to adopt multi-font document. Proposed method has been proved by the results of experiment the fact that the distinction probability of the Korean and English is more than 90%.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.12
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• pp.894-906
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• 2006

There are many difficulties to develop a mobile contents due to many constraints on mobile environments. It is difficult to make a good mobile contents with only visual reduction of existing contents on wire Internet. Therefore, it is essential to devise the data representation and to develop the authoring tool to meet the needs of the mobile contents market. We suggest the compact mobile contents to learn Chinese characters and developed its authoring tool. The animation which our system produces is realistic as if someone writes letters with pen or brush. Moreover, our authoring tool makes a user generate a Chinese character animation easily and rapidly although she or he has not many knowledge in computer graphics, mobile programming or Chinese characters. The method to generate the stroke animation is following: We take basic character shape information represented with several contours from TTF(TrueType Font) and get the information for the stroke segmentation and stroke ordering from simple user input. And then, we decompose whole character shape into some strokes by using polygonal approximation technique. Next, the stroke animation for each stroke is automatically generated by the scan line algorithm ordered by the stroke direction. Finally, the ordered scan lines are compressed into some integers by reducing coordinate redundancy As a result, the stroke animation of our system is even smaller than GIF animation. Our method can be extended to rendering and animation of Hangul or general 2D shape based on vector graphics. We have the plan to find the method to automate the stroke segmentation and ordering without user input.

• Journal of the Korean Graphic Arts Communication Society
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• v.6 no.1
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• pp.41-57
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• 1988

Recently, it Is required to develop OCR(Optical Character Reader) along with the progress of the information processing system for Hangeul. Characters have to be recognized clearly so that OCR can be applied, Structure analysis method and lump method are used for the recognition of characters, and OCR is now available for the recognition of printed characters and handwritten alphanumeric characters having simple structure by them However, It is known that there should be much more study on the development of handwritten Hangout's OCR. This paper proposed a new method for the handwritten Hangout character recognition. The units of Initial consonant of Hangout are separated and then recognized from the utilization of the position- Information of Hangeul's units from the normalized patterns using the regression line theory. It is carried out for the extraction of the block which exists in the virtual Initial consonant region from the normalized input patterns and the calculation on maximum value (${\beta}$) of likelihood after comparing the features of separated subpattern with the initial consonant dictionary.

• Journal of the HCI Society of Korea
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• v.1 no.1
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• pp.21-28
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• 2006

Most of the commercialized wearable text input devices are wrist-worn keyboards that have adopted the minimization method of reducing keys. Generally, a drastic key reduction in order to achieve sufficient wearability increases KSPC(Keystrokes per Character), decreases text entry performance, and requires additional effort to learn a new typing method. We are faced with wearability-usability tradeoff problems in designing a good wearable keyboard. To address this problem, we introduced a new keyboard minimization method of reducing key pitch. From a series of empirical studies, we found the potential of a new method which has a keyboard with a 7mm key pitch, good wearability and social acceptance in terms of physical form factors, and allows users to type 15.0WPM in 3 session trials. However, participants point out that a lack of passive haptic feedback in keying action and visual feedback on users' input deteriorate the text entry performance. We have developed the One-key Keyboard that addresses this problem. The traditional desktop keyboard has one key per character, but the One-key Keyboard has only one key ($70mm{\times}35mm$) on which a 10*5 QWERTY key array is printed. The One-key Keyboard detects the position of the fingertip at the time of the keying event and figures out the character entered. We conducted a text entry performance test comprised of 5 sessions. The participants typed 18.9WPM with a 6.7% error rate over all sessions and achieved up to 24.5WPM. From the experiment's results, the One-key Keyboard was evaluated as a potential text input device for wearable computing, balancing wearability, social acceptance, input speed, and learnability.

• 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.