• Proceedings of the Korean Society for Language and Information Conference
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• 1998.02a
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• pp.283-294
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• 1998

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.361-366
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• 2018

For each character constituting learning data, different fonts are added in pixel unit to create MASK, and then pixel values belonging to the MASK are divided into three groups. The experimental data are modified into skeletal forms, and then regional boundary operation is used to create a boundary that distinguishes the background region adjacent to the skeleton of the character from the background of the modified experimental data. Discordance values between the modified experimental data and the MASKs are calculated, and then the MASK with the minimum value is found. This MASK is selected as a finally recognized result for the given experiment data. The recognition algorithm using skeleton of the character and the regional boundary operation can easily extend the learning data set by adding new fonts to the given learning data, and also it is simple to implement, and high character recognition rate can be obtained.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.456-460
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• 2005

This paper will be examined new character analysis method by the concept of mask. Mask can be identified by wearer or viewer itself. It can be detected the similarity of agent that is represented viewer for putting their emotion. Therefore character and mask take the same role of representing ethers. The result of this study can be evidenced that animation character is possible to be analyzed into the concept of mask and this theory can also be adapted to drama and movie.

• International journal of advanced smart convergence
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• v.8 no.3
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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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.792-794
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• 2014

Character recognition is an image processing technique for obtaining the character information such as documents and automobile license plate and for this edge detection methods are commonly used. The previous edge detection methods are mostly applying the weighted value mask on the image and because it applies the same mask to the entire areas of the image, the processing results are somewhat insufficient. Therefore, this paper has proposed an edge detection algorithm by applying the weighted value mask considering the distribution and location of pixels to be suitable for the character recognition.

• Journal of Mechanical Science and Technology
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• v.20 no.9
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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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• v.6 no.2
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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.

• Journal of the Korean Society of Costume
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• v.64 no.8
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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.

• Proceedings of the IEEK Conference
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• 1998.06a
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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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• v.18 no.3
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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.