• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.186-189
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• 2019

Image inpainting is an image processing technique that restores an image by naturally filling the empty or damaged regions in an image. In this paper, we present a new image inpainting technique that can suppress the generation of texture garbage which is one of the artifacts of existing exemplar-based image inpainting. Unlike the existing technique, only the stationary source patch is sampled as the exemplar patch based on the assumption of spatial stationarity of the texture. This prevents the texture garbage, which is an inconsistent piece of texture from being copied to the target region. Experimental results show that the texture synthesis using the proposed method produces more natural inpainting results than the existing method.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.178-184
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• 2023

AI image generation technology has become a popular research direction in the field of AI, which is widely used in the field of digital art and conceptual design, and can also be used in the process of 3D texture mapping. This paper introduces the production process of 3D texture mapping using AI image technology, and discusses whether it can be used as a new way of 3D texture mapping to enrich the 3D texture mapping production process. Two AI deep learning models, Stable Diffusion and Midjourney, were combined to generate high-quality AI textures. Finally, the lmage to material function of substance 3D Sampler was used to convert the AI-generated textures into PBR 3D texture maps. And applied in 3D environment. This study shows that 3D texture maps generated by AI image generation technology can be used in 3D environment, which not only has short production time and high production efficiency, but also has rich changes in map styles, which can be quickly adjusted and modified according to the design scheme. However, some AI texture maps need to be manually modified before they can be used. With the continuous development of AI technology, there will be great potential for further development and innovation of AI-generated image technology in the 3D content production process in the future.

• Korean Journal of Computational Design and Engineering
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• v.9 no.4
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• pp.397-405
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• 2004

Texture mapping is the process of covering 3D models with texture images in order to increase the visual realism of the models. For proper mapping the coordinates of texture images need to coincide with those of the 3D models. When projective images from the camera are used as texture images, the texture image coordinates are defined by a camera calibration method. The texture image coordinates are determined by the relation between the coordinate systems of the camera image and the 3D object. With the projective camera images, the distortion effect caused by the camera lenses should be compensated in order to get accurate texture coordinates. The distortion effect problem has been dealt with iterative methods, where the camera calibration coefficients are computed first without considering the distortion effect and then modified properly. The methods not only cause to change the position of the camera perspective line in the image plane, but also require more control points. In this paper, a new iterative method is suggested for reducing the error by fixing the principal points in the image plane. The method considers the image distortion effect independently and fixes the values of correction coefficients, with which the distortion coefficients can be computed with fewer control points. It is shown that the camera distortion effects are compensated with fewer numbers of control points than the previous methods and the projective texture mapping results in more realistic image.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.05a
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• pp.99-104
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• 2003

TiN coated films show a good mechanical properties, high thermal properties and wear, erosion and corrosion resistance and are widely used as a coating materials in tools, ornaments, parts and semiconductors. In spite of these good properties, the fracture of TiN coated films occur during use. The fracture of TiN thin films is related to their microstructure. Especially, the life of TiN coated layer is related to the texture of the TiN films. One researcher suggested that the corrosion and erosion resistance of the TiN thin films is related to a uniform and dense structure of films. In this study, we studied the relationships between textures and friction coefficient, erosion and corrosion in TiN coated films. The flatness of (115) texture surface of TiN thin films is flatter than that of (111) texture surface. The friction coefficient of (115) texture surface of TiN thin films is similar with that of (111) texture surface. The wear resistance of (115) texture surface of TiN thin films is better than that of (111) texture surface. The erosion and corrosion resistance of (115) texture surface of TiN thin films is better than that of (111) torture surface. As well as texture, the wear, erosion and corrosion of TiN thin films has to consider defects such as pinholes, cracks, surface roughness and open columnar structure. The life of TiN coated products is influenced by the properties of wear, erosion, and corrosion resistance of TiN thin films and is related to texture of TiN coated films, density of pinholes and cracks, density of structure, and surface flatness.

• The Research Journal of the Costume Culture
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• v.19 no.3
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• pp.556-564
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• 2011

The purpose of this study was to analyze the effect of the structural properties, the color characteristics and the texture of sight and touch on the tactile preferences for the black fabrics. Male and female university students were asked to evaluate the texture of sight and touch and tactile preference to the nine different black fabrics which were selected on the basis of the previous research results. Data were analyzed by using frequency analysis, mean, factor analysis, t-test, F-test, correlation and regression analysis. The texture of sight and touch for black fabrics was classified into four factors: smoothness, bulkiness, extensibility, firmness. This texture of sight and touch factors showed a significant correlative relationship to the structural properties and color characteristics of the black fabrics. There were significant differences according to black fabrics on the point of texture of sight and touch. The velvet was evaluated the most smooth fabric, while the velvet and fake leather were evaluated the most bulky fabrics. Also, the jersey and lace fabrics were evaluated the most extensible fabrics, while the melton was evaluated as the most firm fabrics. There were significant correlative relationships not only between the structural properties and the texture of sight and touch but also between the color characteristics and the texture for black fabrics. Also, among the structural properties, the color characteristics and the texture of sight and touch of black fabrics, major variable factor of influencing on the tactile preference was turned out to be the texture of sight and touch.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.327-336
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• 2002

Texture analysis is an important technique in many image understanding areas, such as perception of surface, object, shape and depth. But the previous works are intend to the issue of only texture segment, that is not capable of acquiring recognition information. No unsupervised method is basased on the recognition of texture in image. we propose a novel approach for efficient texture image analysis that uses unsupervised learning schemes for the texture recognition. The self-organization neural network for multiple texture image identification is based on block-based clustering and merging. The texture features used are the angle and magnitude in orientation-field that might be different from the sample textures. In order to show the performance of the proposed system, After we have attempted to build a various texture images. The final segmentation is achieved by using efficient edge detection algorithm applying to block-based dilation. The experimental results show that the performance of the system Is very successful.

• The Journal of Natural Sciences
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• v.4
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• pp.191-220
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• 1991

A new texture segmentation-based image coding technique which performs segmentation based on roughness of textural regions and properties of the human visual system (HVS) is presented. This method solves the problems of a segmentation-based image coding technique with constant segments by proposing a methodology for segmenting an image texturally homogeneous regions with respect to the degree of roughness as perceived by the HVS. The fractal dimension is used to measure the roughness of the textural regions. The segmentation is accomplished by thresholding the fractal dimension so that textural regions are classified into three texture classes; perceived constant intensity, smooth texture, and rough texture. An image coding system with high compression and good image quality is achieved by developing an efficient coding technique for each segment boundary and each texture class. For the boundaries, a binary image representing all the boundaries is created. For regions belonging to perceived constant intensity, only the mean intensity values need to be transmitted. The smooth and rough texture regions are modeled first using polynomial functions, so only the coefficients characterizing the polynomial functions need to be transmitted. The bounda-ries, the means and the polynomial functions are then each encoded using an errorless coding scheme. Good quality reconstructed images are obtained with about 0.08 to 0.3 bit per pixel for three different types of imagery ; a head and shoulder image with little texture variation, a complex image with many edges, and a natural outdoor image with highly textured areas.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.311-320
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• 2003

The Optimal filter yielding optimal texture feature separation is a most effective technique for extracting the texture objects from multiple textures images. But, most optimal filter design approaches are restricted to the issue of supervised problems. No full-unsupervised method is based on the recognition of texture objects in image. We propose a novel approach that uses unsupervised learning schemes for efficient texture image analysis, and the band-pass feature of Gabor-filter is used for the optimal filter design. In our approach, the self-organizing neural network for multiple texture image identification is based on block-based clustering. The optimal frequency of Gabor-filter is turned to the optimal frequency of the distinct texture in frequency domain by analyzing the spatial frequency. In order to show the performance of the designed filters, after we have attempted to build a various texture images. The texture objects extraction is achieved by using the designed Gabor-filter. Our experimental results show that the performance of the system is very successful.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2008.10a
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• pp.130-133
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• 2008

The formability of DP steels can be affected by not only initial texture but also deformation texture evolved during plastic deformation. To investigate the evolution of deformation texture during deep drawing, deep drawing process for DP steels was carried out experimentally. A rate sensitive polycrystal model was used to predict texture evolution during deep drawing process. In order to evaluate the strain path during deep drawing, a steady state was assumed in the flange part of deep drawn cup. A rate sensitive polycrystal model successfully predicted the texture development in DP steels during deep drawing process. It was found that the final stable orientations were strongly dependent on the initial location in the blank.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.14-16
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• 2004

Although there have been wide range of studies to characterize forest stands based upon spectral information of satellite image, it was not fully understood the texture information of forest stand using high resolution data. The objective of this study is to evaluate several texture measures for characterizing forest stand structure, such as species composition, diameter at breast height(DBH), stand density, and age. High resolution IKONOS satellite imagery data were acquired in August 200 lover the forested area near Ulsan, Korea. Primary forest types were plantation pine, mixed forest, and natural deciduous forest of stand age ranging from 10 to 50 years old. Several GLCM-based texture measures were compared with forest stand characteristics. In overall, a texture measure (contrast) calculated using red band were better to differentiate species and age group than other texture measures and near infrared bands.