• Transactions of Materials Processing
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• v.7 no.5
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• pp.459-464
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• 1998

Effect of the several initial textures such as random texture, rolling texture and cube texture, on the plane strain stretching was studied by interpretation of the finite element method. The calculation of yield locus indicated that the sheet oriented in the cube texture exhibits easy yielding on uniaxial stress state whereas the sheet having either a random or the rolling texture exhibits easy yielding on shear deformation. Upon stretching tests, the thickness strain at the center region contacting the punch was identical regardless of the initial textures while the dependence of the thickness strain on the initial texture was found in the other regions. In general punch loads required or the sheet with an initial cube texture was as expected from calculated yield locus, lower than those for the others.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.40-48
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• 2007

This paper presents a novel texture segmentation method using multilayer perceptron (MLP) networks and Markov random fields in multiscale Bayesian framework. Multiscale wavelet coefficients are used as input for the neural networks. The output of the neural network is modeled as a posterior probability. Texture classification at each scale is performed by the posterior probabilities from MLP networks and MAP (maximum a posterior) classification. Then, in order to obtain the more improved segmentation result at the finest scale, our proposed method fuses the multiscale MAP classifications sequentially from coarse to fine scales. This process is done by computing the MAP classification given the classification at one scale and a priori knowledge regarding contextual information which is extracted from the adjacent coarser scale classification. In this fusion process, the MRF (Markov random field) prior distribution and Gibbs sampler are used, where the MRF model serves as the smoothness constraint and the Gibbs sampler acts as the MAP classifier. The proposed segmentation method shows better performance than texture segmentation using the HMT (Hidden Markov trees) model and HMTseg.

• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.335-344
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• 2001

Texture is extensively studied in a variety of image processing applications such as image segmentation and classification because it is an important property to perceive regions and surfaces. This paper focused on the analysis and synthesis of textured single and multiband images using Markov Random Field model considering the existent spatial correlation. Especially, for multiband images, the cross-channel correlation existing between bands as well as the spatial correlation within band should be considered in the model. Although a local interaction is assumed between the specified neighboring pixels in MRF models, during the maximization process, short-term correlations among neighboring pixels develop into long-term correlations. This result in exhibiting phase transition. In this research, the role of temperature to obtain the most probable state during the sampling procedure in discrete Markov Random Fields and the stopping rule were also studied.

• Journal of Sensor Science and Technology
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• v.32 no.1
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• pp.10-15
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• 2023

It is well known that polycrystalline ceramics fabricated via the templated grain growth method along a desired crystallographic direction, generally along [001], exhibits enhanced piezoelectric response. Generally, the piezoelectric properties of textured ceramics depend on the degree of texture, as piezoelectric properties peak in single crystals. Therefore, understanding the relationship between the degree of texture and piezoelectric properties is fundamental. Here, we present state-of-the-art textured piezoceramics by focusing on critical issues such as the quality of templates used for texturing and proper evaluation of the degree of texture analysis. The relationship between the degree of texture and its impact on the properties of textured materials is exclusively defined by the Lotgering factor (L.F.) calculated from the X-ray diffraction profiles. Additionally, we show that L.F. is not a suitable indicator of the degree of texture, contrary to previous interpretations. This statement was further supported by the fact that the true degree of texture can be better quantified by the multiples of random distribution. This argument was justified by comparing the quantitative values of the degree of texture obtained from both methods to those of the piezoelectric charge coefficient of textured and random ceramics.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.444-449
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• 1996

The semiconductor, which is precision product, requires many inspection processes. The surface conditions of the semiconductor chip affect on the functions of the semiconductors. The defects of the chip surface are cracks or voids. As general inspection method requires many inspection procedure, the inspection system which searches immediately and precisely the defects of the semiconductor chip surface is required. We suggest the detection algorithm for inspecting the surface defects of the semiconductor surface. The proposed algorithm first regards the semiconductor surface as random texture and point spread function, and secondly presents the character of texture by linear estimation theorem. This paper assumes that the gray level of each pixel of an image is estimated from a weighted sum of gray levels of its neighbor pixels by linear estimation theorem. The weight coefficients are determined so that the mean square error is minimized. The obtained estimation window(two-dimensional estimation window) characterizes the surface texture of semiconductor and is used to discriminate the defects of semiconductor surface.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.9
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• pp.76-90
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• 1999

In this paper, a color image retrieval algorithm is proposed based on color histogram and color texture. The representative color vectors of a color image are made from k-means clustering of its color histogram, and color texture is generated by centering around the color of pixels with its color vector. Thus the color texture means texture properties emphasized by its color histogram, and it is analyzed by Gaussian Markov Random Field (GMRF) model. The proposed algorithm can work efficiently because it does not require any low level image processing such as segmentation or edge detection, so it outperforms the traditional algorithms which use color histogram only or texture properties come from image intensity.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.6
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• pp.89-96
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• 1989

An improved method on texture coding, which is a part of the region growing based image coding, is presented in this paper. An image is segmented into stochastic regions which can be described as a stochastic random field, and non-stochastic ones in order to efficiently represent texture. In the texture coding and reconstruction, an autoregressive model is used for the stochastic regions, while a two-dimensional polynomial approximation is used for the non-stochastic ones. This proposed method leads to a better subjective quality, relatively higher compression ratio and shorter processing time for coding and reconstructing than the conventional method which uses only two-dimensional polynomial approximation.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.8
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• pp.1238-1246
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• 1989

In this paper, a texture synthesis technique based on the NCAR(non-causal auto-regressive) model and the pyramid structure is proposed. In order to estimate the NCAR model parameters accurately from a noisy texture, the MAP(maximum a posteriori) estimation technique is also employed. In our approach, since the input texture is decomposed into the Laplacian oyramid planes first and then the NCAR model is applied to each plane, we are able to obtain a good synthesized texture even if the texture exhibits some non-random local structure or non-homogenity. The usrfulness of the proposed method is demonstrated with seveal real textures in the Brodatz album. Finally, the 2-dimensional MAP estimation technique can be used to the image restoration for noisy images as well as a texture image synthesis.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2004.10a
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• pp.215-217
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• 2004

In order to obtain the initial starting sample having a random texture and fine grains, aluminum alloy 3103 sheets were repeatedly deformed by CCSS up to six passages and subsequently annealed at $300^{\circ}C$ for 1h. These samples were cold rolled at room temperature and also warm rolled at $250^{\circ}C$. Changes in rolling temperature gave rise to the different texture evolution. Warm rolling led to the pronounced texture gradients comprising the shear texture at the surface and the rolling texture at the sheet center. The formation of the rolling texture components, i.e., the ${\beta}$-fiber, was promoted by cold rolling than warm rolling.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1998.03a
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• pp.242-245
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• 1998

Effects of the anisotrpy due to the initial textures in the plane sheet on plane strain punch stretching has been investigated. In this study, the anisotropy from textures in the sheet is incoporated into the finite element process model by combining the theory of crstal plasticity. Three different textures such as random texture, plane strain compression texture and cube texture are considered. Variations of puch loads as well as thickness distributions of the sheets with three different initial textures are investigated.