• 한국언어정보학회:학술대회논문집
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• 한국언어정보학회 1998년도 Language, Information and Computation = Selected Papers from the 12th Pacific Asia Conference on Language, Information and Computation, Singapore
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• pp.283-294
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• 1998

• 문화기술의 융합
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• 제4권4호
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• pp.361-366
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• 2018

학습 데이터를 구성하는 각각의 문자들에 대해 서로 다른 글자체들을 픽셀 단위로 더해서 MASK를 만들고, 해당 MASK에 속하는 픽셀값들을 세 영역으로 나눈다. 실험 데이터를 골격 형태로 수정하고, 지역 경계 연산을 사용하여 수정된 실험 데이터의 배경 중에서 문자의 골격에 인접한 배경 영역을 구분하는 경계를 만든다. 수정된 실험 데이터와 MASK들 간의 불일치 정도를 계산해서 최소값을 가지는 MASK를 찾는다. 이 MASK가 해당 실험 데이터에 대해 최종적으로 인식된 학습 데이터 문자로 선택된다. 문자의 골격과 지역 경계 연산을 사용하는 인식법은 주어진 학습 데이터에 새로운 글자체를 추가해서 학습 데이터를 쉽게 확장할 수 있으며, 구현하기가 간단하면서도 높은 문자 인식률을 얻을 수 있다.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2005년도 추계 종합학술대회 논문집
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• pp.456-460
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• 2005

본 연구는 애니메이션의 캐릭터 분석을 위한 새로운 방법으로 마스크를 통한 의미 파악이다. 마스크는 착용자에 의해서 또는 관객의 동일시에 의해 자신과 합일을 이룬다. 캐릭터를 자신의 대리자로 여기며 자신의 감정을 이입하는 개념은 마스크적 역할과 유사성을 가질 수 있다. 마스크의 다양한 역할 역시 애니메이션의 캐릭터가 행하는 역할과 유사하다. 즉 마스크의 역할은 풍요 제의, 벽사, 신성, 의술, 추억, 영혼, 전쟁, 장례, 입사, 토템, 기우, 수렵, 무용과 연극의 예능 등을 위해 사용된다. 연구 결과 마스크의 성질과 애니메이션뿐만 아니라 영화나 연극의 배우까지 포괄적으로 포함하여 마스크의 개념으로 수용된다.

• International journal of advanced smart convergence
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• 제8권3호
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• pp.131-137
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• 2019

This study proposes a method of learning and recognizing the characteristics that are the classification criteria of Hangul using Mask R-CNN, one of the deep learning techniques, to recognize and classify atypical Hangul characters. The atypical characters on the Hangul signboard have a lot of deformed and colorful shapes beyond the general characters. Therefore, in order to recognize the Hangul signboard character, it is necessary to learn a separate atypical Hangul character rather than the existing formulaic one. We selected the Hangul character '닭' as sample data and constructed 5,383 Hangul image data sets and used them for learning and verifying the deep learning model. The accuracy of the results of analyzing the performance of the learning model using the test set constructed to verify the reliability of the learning model was about 92.65% (the area detection rate). Therefore we confirmed that the proposed method is very useful for Hangul signboard character recognition, and we plan to extend it to various Hangul data.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 추계학술대회
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• pp.792-794
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• 2014

문자인식은 문서 및 자동차 번호판 등의 문자정보를 얻는 영상처리 기술이며, 이를 위하여 에지를 검출하는 방법이 주로 사용되고 있다. 기존의 에지검출 방법은 대부분 영상에 가중치 마스크를 적용하는 방법이며, 영상의 전체 영역에 동일한 마스크를 적용하므로 처리결과가 다소 미흡하다. 따라서 본 논문은 문자인식에 적합하도록 화소의 분포 및 위치를 고려한 가중치 마스크를 적용하여 에지검출 알고리즘을 제안하였다.

• Journal of Mechanical Science and Technology
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• 제20권9호
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• pp.1361-1370
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• 2006

An electronic beam mis-landing phenomenon on the RGB (red/green/blue) -fluorescent surface has been considered as one of serious problems to be solved in cathode-ray tube (CRT), which is generally caused by mechanical shock and vibration. In this work, structural design concepts on the major parts of the CRT, such as a frame, a shadow mask, and a spring, are studied to improve the mechanical shockproof character of a CRT by FEM-analyses and experimental approaches ; a frame is newly designed to have strength employing the double-corner-beads which reduces considerably the distortion of the frame and the shadow mask : the edge-bead of a shadow-mask is redesigned to maintain the wide curved surface of a shadow-mask after mechanical shock : finally, a spring supporting the frame and the shadow-mask is designed to have enough flexibility along drop-direction. As an example, a conventional type of a 15inch CRT was utilized to demonstrate the feasibility and usefulness of this work. Overall, some favorable information on the structural design of the CRT is achieved, and the mechanical shockproof character of a 15-inch CRT is improved in the degree of 3G $(1G=9.81m/s^2)$ as an average-value.

• International Journal of Advanced Culture Technology
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• 제6권2호
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• pp.123-128
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• 2018

Learning data is composed of 100 characters with 10 different fonts, and test data is composed of 10 characters with a new font that is not used for the learning data. In order to consider the variety of learning data with several different fonts, 10 learning masks are constructed by accumulating pixel values of same characters with 10 different fonts. This process eliminates minute difference of characters with different fonts. After finding maximum values of learning masks, test data is expanded by multiplying these maximum values to the test data. The algorithm calculates sum of differences of two corresponding pixel values of the expanded test data and the learning masks. The learning mask with the smallest value among these 10 calculated sums is selected as the result of the recognition process for the test data. The proposed algorithm can recognize various types of fonts, and the learning data can be modified easily by adding a new font. Also, the recognition process is easy to understand, and the algorithm makes satisfactory results for character recognition.

• 복식
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• 제64권8호
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• pp.124-137
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• 2014

The purpose of this study is to produce an essential guideline for making costumes for traditional Korean mask plays by doing a comparative analysis between traditional Korean mask plays and Italian 'Commedia dell'arte'. The results of this study are as follow. The costumes of Korea's mask plays were mainly used to show difference in social status. Analysis showed that costume features, such as color, fabric, and silhouette, were not important to the traits of the character. On the other hand, the costumes in the Italian 'Commedia dell'arte' were used to express the characters' traits. The colors, fabric and silhouettes were exaggerated compared to everyday wear. This enhanced the looks of the character, and it kept on developing with the demands of the culture consumer. This study was performed to support further development and success of traditional Korean mask plays.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 하계종합학술대회논문집
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• pp.913-916
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• 1998

In this paper, to provide the robustness of character recognition, we propose a recognition method using the dilated boundary curve feature which has the invariance characteristics for the shift, scale, and rotation changes of character pattern. And its some characteristics and effectieness are evaluated through the experiments for both the english alphabets and the numeral digits. The feature vector is represented by the fourier descriptor for a boundary curve of the dilated character pattern which is generated by the circular mask dilation method, and is used for a nearest neighbort classifier(NNC) or a nearest neighbor mean classifier(NNMC). These the processing time and the recognition rate, and take also the robustness of recognition for both some internal noise and partial corruption of an image pattern.

• Journal of Information Processing Systems
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• 제18권3호
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• pp.411-427
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• 2022

Digging historical and cultural information from seals in ancient books is of great significance. However, ancient Chinese seal samples are scarce and carving methods are diverse, and traditional digital image processing methods based on greyscale have difficulty achieving superior segmentation and recognition performance. Recently, some deep learning algorithms have been proposed to address this problem; however, current neural networks are difficult to train owing to the lack of datasets. To solve the afore-mentioned problems, we proposed an SEL-RefineMask which combines selector of feature pyramid network (SEL-FPN) with RefineMask to segment and recognize seals. We designed an SEL-FPN to intelligently select a specific layer which represents different scales in the FPN and reduces the number of anchor frames. We performed experiments on some instance segmentation networks as the baseline method, and the top-1 segmentation result of 64.93% is 5.73% higher than that of humans. The top-1 result of the SEL-RefineMask network reached 67.96% which surpassed the baseline results. After segmentation, a vision transformer was used to recognize the segmentation output, and the accuracy reached 91%. Furthermore, a dataset of seals in ancient Chinese books (SACB) for segmentation and small seal font (SSF) for recognition were established which are publicly available on the website.