• Journal of the Korean Wood Science and Technology
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• v.50 no.6
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• pp.490-498
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• 2022

The current study aimed to verify the image segmentation ability of rays in tangential thin sections of conifers using artificial intelligence technology. The applied model was Mask region-based convolutional neural network (Mask R-CNN) and softwoods (viz. Picea jezoensis, Larix gmelinii, Abies nephrolepis, Abies koreana, Ginkgo biloba, Taxus cuspidata, Cryptomeria japonica, Cedrus deodara, Pinus koraiensis) were selected for the study. To take digital pictures, thin sections of thickness 10-15 ㎛ were cut using a microtome, and then stained using a 1:1 mixture of 0.5% astra blue and 1% safranin. In the digital images, rays were selected as detection objects, and Computer Vision Annotation Tool was used to annotate the rays in the training images taken from the tangential sections of the woods. The performance of the Mask R-CNN applied to select rays was as high as 0.837 mean average precision and saving the time more than half of that required for Ground Truth. During the image analysis process, however, division of the rays into two or more rays occurred. This caused some errors in the measurement of the ray height. To improve the image processing algorithms, further work on combining the fragments of a ray into one ray segment, and increasing the precision of the boundary between rays and the neighboring tissues is required.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.439-446
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• 2021

This study was to investigate whether there are differences in subjective bad breath-related characteristics and psychological characteristics of sports masks printed with natural minerals compared with quarantine masks and cotton masks. The study subjects were divided into 30 people in the Sports Mask Group, 30 people in the KF Mask Group (KMG), and 30 people in the cotton mask group (CMG), and a total of 90 subjects participated in the study. It was randomly sent to use 1 mask per day and 3 masks for 3 days. The study period was conducted from October 15, 2020 to October 30, 2020. As a result of the study, there was no difference in the use of masks between the three groups in terms of bad breath health and dry mouth. However, the sports mask was superior to other masks in oral respiration and bad breath angle. As a result of analyzing psychological factors, there was no difference between the 3 groups for depression. However, in the stress factor, sports masks were superior to other masks in stress. The results of this study are valuable as suggesting the direction of use of functional masks, and we hope that they will be used as basic data for functional mask research to be studied in the future.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.851-854
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• 2000

Digital halftoning is a technique to make an equivalent binary image from scanned photo or graphic images. Low pass filtering characteristic of human visual system can be applied to get the effect of spatial averaging of local area consisted of black and white pixels for gray image. The overlapping of black dot decreases brightness and black dot is very sensitive to human visual system in the bright region. In this paper, for gray-level expression, only bright gray region in the color image is considered for blue noise mask (BNM) approach. To solve this problem, BNM with CMY dot is used for the bright region instead of black dot. Dot-on-dot model with single mask causes the problem making much black dot overlap, color distortion. Therefore approach with three masks for C, M and Y each is proposed to decrease pixel overlap and color distortion.

• The Research Journal of the Costume Culture
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• v.30 no.3
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• pp.455-476
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• 2022

The aim of this study was to develop Jiangxi Nuo masks using 3D digital fashion design technology and suggest various ways to utilize traditional culture based on the characteristics of Nuo masks, a traditional Chinese artifact of intangible cultural significance. The researchers conducted a literature review to gather information about Nuo culture and masks that could represent Jiangxi. Features of the masks were analyzed and classified. The result are as follows. First, the symbolic characteristics of Jiangxi's Nuo masks can be divided into those based on their origin and history, the user's social status, and the notions of primitive beliefs of the chosen people, such as naturism and totemism. Second, Nuo masks' splendid decorations convey meanings such as luck, the bixie, longevity, wealth, and peace in the family. Third, playfulness in mask-making is about dismantling the original form of the mask, re-creating it through application. Fourth, the masks express primitiveness mostly by conserving the wood's original color or material. The initial masks carved to represent images of figures aptly deliver the primitive forms and images of Nuo culture. In this study, Nuo masks were developed and produced using the 3D digital technology CLO 3D by adopting the expressive characteristics and applying design methods such as asymmetricity, exaggeration, and modification. The results of this study demonstrate the possibility of creating diverse as well as economical designs through the reduction of production.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.259-266
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• 2013

Binary connected-components labeling, which is widely used in the field of the pattern recognition, has been researched for a long time as one of the basic image processing techniques. Two-scan algorithm has been mainly used in the researches of the connected-components labeling. Recently, for the first scan in the two-scan algorithm, block-based labeling approaches have been used and reported as the fastest methods. In this paper, a new efficient scan mask for connected-components labeling with a block-based labeling approach is proposed. Labeling with the new pixel-based scan mask is more efficient than any other existing method. The results of the experiments show that the proposed method is faster than the existing fastest method.

• Korean Journal of Artificial Intelligence
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• v.9 no.2
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• pp.7-14
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• 2021

Purpose: To solve urban problems, empirical research is being actively conducted to implement a smart city based on various ICT technologies, and digital twin technology is needed to effectively implement a smart city. A digital twin is essential for the realization of a smart city. A digital twin is a virtual environment that intuitively visualizes multidimensional data in the real world based on 3D. Digital twin is implemented on the premise of the convergence of GIS and BIM, and in particular, a lot of time is invested in data pre-processing and labeling in the data construction process. In digital twin, data quality is prioritized for consistency with reality, but there is a limit to data inspection with the naked eye. Therefore, in order to improve the required time and quality of digital twin construction, it was attempted to detect a building using Mask R-CNN, a deep learning-based masking algorithm for aerial images. If the results of this study are advanced and used to build digital twin data, it is thought that a high-quality smart city can be realized.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.630-632
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• 2012

Contemporary society has evolved in the digital information age. Because of this, use of various digital images has been increased. To process these images, various digital image processing methods are used. Edge detection methods, one of those, are utilized to various areas of application such as object recognition, line detection. To detect edge, there are many methods such as Sobel, Prewitt, Laplacian. Because images which are dealt with existing methods are processed in same methods regardless the distribution of gray-level in image, edge detection property is insufficient. Therefore, In this study, to improve shortcomings of existing methods an algorithm using modified expansion mask is proposed.

• Journal of the Korean Graphic Arts Communication Society
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• v.16 no.3
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• pp.81-95
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• 1998

If a image doesn't include sufficient data of output size and resolution, we will scan again the image. Interpolation generates a new pixel by methematical average of processing. In the interpolation method, there are nearest neighbor interpolation, bilinear interpolation and bicubic interpolation etc. This study was carried out for the purpose of researching compatible method to digital scan image caused by only different interpolation methods. Nearest neighbor interpolation show superior effect in the drawing image. Bilinear interpolation show reduction in detail and contrast. Bicubic interpolation show superior effect in the digital photo image USM(Unsharp Mask) application after extension by interpolation show better than extension by interpolation after USM(unsharp mask) application.

• Transactions on Electrical and Electronic Materials
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• v.15 no.4
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• pp.230-234
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• 2014

Automatic detection of disease helps medical institutions that are introducing digital images to read images rapidly and accurately, and is thus applicable to lesion diagnosis and treatment. The aim of this study was to apply a symmetry contribution algorithm to unsharp mask filter-applied MR images and propose an analysis technique to automatically recognize brain tumor and edema. We extracted the skull region and drawed outline of the skull in database of images obtained at P University Hospital and detected an axis of symmetry with cerebral characteristics. A symmetry contribution algorithm was then applied to the images around the axis of symmetry to observe intensity changes in pixels and detect disease areas. When we did not use the unsharp mask filter, a brain tumor was detected in 60 of a total of 95 MR images. The disease detection rate for the brain was 63.16%. However, when we used the unsharp mask filter, the tumor was detected in 87 of a total of 95 MR images, with a disease detection rate of 91.58%. When the unsharp mask filter was used in the pre-process stage, the disease detection rate for the brain was higher than when it was not used. We confirmed that unsharp mask filter can be used to rapidly and accurately to read many MR images stored in a database.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.892-894
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• 2013

Edge has been utilized in various application fields with development of technique of digital image processing. In conventional edge detection methods, there are some methods using mask including Sobel, Prewitt, Roberts and Laplacian operator. Those methods are that implement is simple but generates errors of edge detection in images added AWGN(additive white Gaussian noise). Therefore, to compensate the defect of those methods, in this paper, an edge detection algorithm using modified mask is proposed, and it showed superior edge detection property in AWGN.