• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.8
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• pp.1142-1152
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• 2004

The purpose of this study is to verify the visual perception on various cotton fabrics of the same color. Results obtained through subjective evaluation of cotton fabrics showed that the textural adjectives could be classified into 3; warm/cool, flexibility and surface property, the sensibility adjectives into 5; simple, attractive, masculine, conservative, comfortable and visual perception adjectives into 6; hard, warm, smooth, brilliant, classic and casual. Image distribution results on 12 different fabrics, showed different distributions among textiles on visual perception due to varying texture and sensibility. In thickness, weight, weave type, bending and surface characteristics which are structure characteristics, significant differences were shown for visual perception examination. Having placed into an image scale, visual perception dimension developed divided into the ＇soft-hard＇ axis and the ＇warm-cool＇ axis.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.626-629
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• 2004

Texture imaging, which means texture image creation by co-occurrence relation, has been known as one of useful image analysis methodologies. For this purpose, most commercial remote sensing software provides texture analysis function named GLCM (Grey Level Co-occurrence Matrix). In this study, texture-imaging program for GLCM algorithm is newly implemented in the MS Visual IDE environment. While, additional texture imaging modules based on GLDV (Grey Level Difference Vector) are contained in this program. As for GLCM/GLDV texture variables, it composed of six types of second order texture function in the several quantization levels of 2(binary image), 8, and 16: Homogeneity, Dissimilarity, Energy, Entropy, Angular Second Moment, and Contrast. As for co-occurrence directionality, four directions are provided as $E-W(0^{\circ}),\;N-E(45^{\circ}),\;S-W(135^{\circ}),\;and\;N-S(90^{\circ}),$ and W-E direction is also considered in the negative direction of E- W direction. While, two direction modes are provided in this program: Omni-mode and Circular mode. Omni-mode is to compute all direction to avoid directionality problem, and circular direction is to compute texture variables by circular direction surrounding target pixel. At the second phase of this study, some examples with artificial image and actual satellite imagery are carried out to demonstrate effectiveness of texture imaging or to help texture image interpretation. As the reference, most previous studies related to texture image analysis have been used for the classification purpose, but this study aims at the creation and general uses of texture image for urban remote sensing.

• Journal of Korea Multimedia Society
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• v.5 no.1
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• pp.94-104
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• 2002

This paper presents a new way of texture mapping on the Genus N object constructed over a single domain. The problem of 2D texture mapping is the discontinuity of texture domain at the virtual boundary on the object. Such phenomenon decreases smoothness of the object as well as looks unnatural. Especially it is necessary for the Genus N object of infinite coninuity to apply the seamless texture mapping. For seamless texture mapping, a multiperiodic function, which transforms a discontinuous function into a continuous function, is suggested. In some applications, however, the visual seams on the textured object provide more realistic appearance. Therefore, this research supports the interactive control from the discontinuity and the continuity across the boundary using the coefficient of the weight function.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.10
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• pp.928-935
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• 2013

In this paper, real-time polygon generation algorithm of 3D point cloud data and texture mapping for tele-operation is proposed. In a tele-operation, it is essential to provide more highly realistic visual information to a tele-operator. By using 3D point cloud data, the tele-operator can observe the working environment from various view point with a reconstructed 3D environment. However, there are huge empty space in 3D point cloud data, since there is no environmental information among the points. This empty space is not suitable for an environmental information. Therefore, real-time polygon generation algorithm of 3D point cloud data and texture mapping is presented to provide more highly realistic visual information to the tele-operator. The 3D environment reconstructed from the 3D point cloud data with texture mapped polygons is the crucial part of the tele-operation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.647-650
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• 2009

In recent years, an understanding and concern about the Photo Realistic CG increased while the CG industry grew. The overall understanding of a system, an output and algorithm, and etc. are needed in order to implement the Photo Realistic CG. Moreover, for the realistic output on CG, the texture task that it is logical the various environment condition according to the physical environment and time, and etc.s has to show. For carrying out the Photo Realistic CG texture task, the extensity of a texture, the physical properties, a material, and an environment, the various access and the logical analysis are needed. Analyzed data reaches the direct affect to the final product for expressing. The realistic ancient history site, and the cultural inheritance and industrial product will be implemented with the ground of the research of the upper part in the imaginary realistic world.

• Journal of Multimedia Information System
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• v.9 no.1
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• pp.1-10
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• 2022

China is a big country in animal fur industry. The total production and consumption of fur are increasing year by year. However, the recognition of fur in the fur production process still mainly relies on the visual identification of skilled workers, and the stability and consistency of products cannot be guaranteed. In response to this problem, this paper proposes a feature fusion-based animal fur recognition network on the basis of typical convolutional neural network structure, relying on rapidly developing deep learning techniques. This network superimposes texture feature - the most prominent feature of fur image - into the channel dimension of input image. The output feature map of the first layer convolution is inverted to obtain the inverted feature map and concat it into the original output feature map, then Leaky ReLU is used for activation, which makes full use of the texture information of fur image and the inverted feature information. Experimental results show that the algorithm improves the recognition accuracy by 9.08% on Fur_Recognition dataset and 6.41% on CIFAR-10 dataset. The algorithm in this paper can change the current situation that fur recognition relies on manual visual method to classify, and can lay foundation for improving the efficiency of fur production technology.

• Korean Institute of Interior Design Journal
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• v.24 no.5
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• pp.99-107
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• 2015

The purpose of this study is to analyze the change of visual stimulus of users to the space through the experiment of EEG and the satisfaction of users depends on the lighting. To do that, the results measured with EEG experiment focusing on Beta ${\beta}$ were compared to each other to figure out difference in the changes of the activation of human brain on lighting's situation as the lighting off and on in the same space. The difference in the results was verified according to the characteristic of users which classified with 4 types of the spatial sensitivities. The results of this study are as following. Firstly, the spacial sensitivity of user is to communicate well with the different senses with stimulus through interaction among the elements. At this time, the brain plays a major role in build the spacial sensitivity of users as the place to make form. Secondly, there are the differences in the activation of brain depends on lighting situation even in the same space. The stimulus into the brain became generally stronger in images with lighting on than off. Especially, the response in the occipital lobe which connected with the visual center turn out strongly in the image of 'modern natural'. Because the visual stimulus interact well with the bright color, the reflectional texture and the rough texture painted the dark color. Thirdly, the satisfaction of users changed with lighting in the space. But we could know that the satisfaction of users isn't be related to the visual stimulus through the results of this study. Finally, there isn't the difference in the activation degree of brain according to the characteristic which are preference of users into 4 types of the spatial sensitivity through the results came from ANCOVA(analysis of covariance) with SPSS Program 22.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.6
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• pp.101-109
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• 2004

This paper proposes an adaptive watermarking algerian technique concerning the visual characteristics of human. To embed watermark to an image, features such as contrast, brightness, and texture are used. The propose method adaptively select blocks and determine the position and intensity of watermark to be applied, concerning the visual characteristics of a human. The experiment involves cropping, image enhancement, low pass filtering, and JPEG compression, which are compared on detectability of watermark against image manipulation and attack

• Current Optics and Photonics
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• v.4 no.3
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• pp.200-209
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• 2020

We describe an approach that uses a bilateral filter to reduce the ringing artifact in motion-blurred restoration image. It takes into account the specific physical structure of the ringing artifact combined with the properties of the human visual system. To properly reduce the ringing artifact, each of the adjacent pixels is limited in a straight line which has a given direction. To protect the edges and the texture regions of an image, our algorithm divides the image into texture regions and flat regions, and the artifact reduction algorithm is only applied to the flat region. Finally, we use 8 typical images and 5 objective quality evaluation indices to evaluate our algorithm. Experimental results show that our algorithm can obtain better results in subjective visual effect and in objective image quality evaluation.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2E
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• pp.85-91
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• 1996

New very low bit rate segmentation video image coding technique is proposed by segmenting image into textually homogeneous regions. Regions are classified into one of three perceptually distinct texture classes(perceived constant intensity, smooth texture, and rough texture) using the Human Visual System(HVS) and the fractals. To design very low bit rate video image coder, it is very important to determine the best block size for estimation the fractal dimension and the thresholding of the fractal dimension for each texture class. Good quality reconstructed images are obtained with about 0.10 to 0.21 bit per pixel(bpp) for many different types of imagery.