• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.316-322
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• 1998

Super precision working technique and machine tool have been developing continually thanks to advanced electronic field. To obtain good result. it is necessary to investigate surface state in grinding with ${\mu}{\textrm}{m}$ level. There were so many researches to satisfy these demands using non-contact methods through the computer vision. In this study, the texture of working surface was analyzed. cooccurrence matrice was obtained from the surface roughness. Texture parameter was obtained by means of position operator compose of $\theta$. d according to variation of angle direction and distance. As a result, it was found that surface texture was more effected by direction ($\theta$) then distance(d).

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.513-518
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• 2000

Surface roughness is one of the most important parameters to estimate quality of products. As this reason. so many studies were carried out through various attempts that were contact or non-contact using computer vision. Even though these efforts, there were few good results in this research. However, texture analysis is making a important role to solve these problems in various fields including universe, aviatiion, living thing and fibers. In this study, texture parameter was obtained by means of position operator according to variation of angle direction and distance. As a result, it was found that surface texture was more effected by direction then distance

• Journal of Biosystems Engineering
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• v.37 no.1
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• pp.28-35
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• 2012

Purpose: This study performed the oscillatory test using the texture analyzer to characterize the viscoelastic behavior of apples such as the storage modulus (E'), the loss modulus (E"), the complex modulus (${\mid}E^*{\mid}$) and the energy dissipated per cycle ($W_{diss}$). Methods: The sinusoidal deformation with the frequency of 1-10 Hz and the maximum displacement of 0.1 mm were applied to the flesh tissues of Fuji, Golden Delicious and Red Delicious apples. The Lissajous figure was used to measure the phase angle(${\delta}$) between stress and strain curve. Results: Trigger force was critical to the measurement of the phase angle. E', E", ${\mid}E^*{\mid}$ and Wdiss were measured using the Lissajous figure and the phase angle. The complex modulus of Golden Delicious apple was significantly lower than those of Fuji apple and Red Delicious apple. Conclusions: Apple flesh was exhibiting more elasticity at low frequency, and more viscosity at high frequency. Dynamic compressive properties of Fuji apple were similar to those of Red Delicious apple but significantly different from those of Golden Delicious apple.

• Journal of Photoscience
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• v.5 no.1
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• pp.11-15
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• 1998

The texture change of non-linear optical molecules at the air/water interface was investigated as a function of surface pressure with Brewster angle microscopy. The texture change resulted from the aggregation of dye molecules is important to understand the film uniformity and grain formation process. The 4-Octadecylhydroxy-4'-nitrostilbene (OHNS) generated the small spots of size around 1$\mu$m. The spots exhibit high contrast with other film area and do not show angle dependent reflectivity change. It is interesting to observe that the size of the domain stays the same as the film pressure increases. At high surface pressure, the contrast ratio of domains becomes high, which means dense packing of OHNS. And, the size of domain grows. In the middle of domain, highly contrasted domains are formed. The first and the second order transitions of OHNS observed from surface pressure-area isotherm result from the two types of grains. The N,N-Dihexadecylcyanoaniline (DHCA) formed highly contrasted gains over entire region, and the grains are the double layers. The difference in Langmuir film of OHNS and DHCA at the air/water interface is consistent with the small tilt angle from the surface normal for OHNS and the large tilt angle for DHCA in the Langmuir-Blodgett films.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2008.05a
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• pp.477-479
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• 2008

Drawability and other mechanical properties of sheet metals are strongly dependent on their crystallographic orientations. In this paper the formability of the AA 5052 Al alloy sheets was investigated after asymmetric rolling and subsequent heat treatment. In most cases, after asymmetric rolling specimens showed a fine grain size and subsequent heat treated specimens showed that the ND//<111> texture component were observed. The anisotropy of formability is often described by the plastic strain ratios (r-value) as a function of the angle to the rolling direction in sheet metal. For a good formability, a high r-value is required in sheet metals. In the asymmetry rolled and subsequent heat treated Al alloy sheet, the variation of the plastic strain ratios have been investigated in this study. The plastic strain ratios of the asymmetry rolled and subsequent heat treated AA 5052 Al alloy sheets were higher than those of the original Al sheets. These could be related to the formation of ND//<111> texture components through asymmetric rolling in Al sheet.

• 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.

• 한국정보디스플레이학회:학술대회논문집
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• 2005.07a
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• pp.338-341
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• 2005

We have examined the aspects of the orientational ordering deformation of ferroelectric liquid crystal during bending performance of plastic substrate by analyzing the polarizing optical microscope texture and the birefringence of the cell. Striped texture becomes more prominent as the radius of curvature of substrate gets smaller. The optic axis of the adjacent stripes domain was not same and the relative angle between them becomes larger as the radius of curvature gets smaller. Especially, the optic axis rotation angle of one domain was lager than the other and the liquid crystal molecules in each domain became more coherent. In addition, the birefringence data with obliquely incident light shows the polar direction shift of liquid crystal molecule by bending performance.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2009.10a
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• pp.354-357
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• 2009

The effect of texture of an extruded OFHC Cu rod on its sliding wear has been explored. Disk specimens with three different orientations were machined from the Cu rod for the wear test; surfaces of the disk were perpendicular ($0^{\circ}$), inclined with a specific angle ($45^{\circ}$), and parallel ($90^{\circ}$) to the extrusion axis of the rod. The texture was analyzed using an X-ray goniometer by measuring {111}, {200}, and {220} pole figures of each specimen. The analyzed texture was correlated with wear-test results of the Cu specimen. Dry sliding wear tests were performed at room temperature using a pin-on-disk wear tester against an Al2O3 ball. Applied load, sliding distance, sliding speed were fixed as 20 N, 200 m, and 0.5 m/sec, respectively. The $45^{\circ}$-inclined (to the extrusion axis) disk specimen showed the lowest wear resistance with the least data scatters. It has been found that distribution of cube texture strongly influences wear rate of the extruded Cu rod.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.698-701
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• 2005

This paper examines that is extracted certain information in forest areas within high resolution imagery based on wavelet transformation. First of all, study areas are selected one more species distributed spots refer to forest type map. Next, study area is cut 256 x 256 pixels size because of image processing problem in large volume data. Prior to wavelet transformation, five texture parameters (contrast, dissimilarity, entropy, homogeneity, Angular Second Moment (ASM≫ calculated by using Gray Level Co-occurrence Matrix (GLCM). Five texture images are set that shifting window size is 3x3, distance .is 1 pixel, and angle is 45 degrees used. Wavelet function is selected Daubechies 4 wavelet basis functions. Result is summarized 3 points; First, Wavelet transformation images derived from contrast, dissimilarity (texture parameters) have on effect on edge elements detection and will have probability used forest road detection. Second, Wavelet fusion images derived from texture parameters and original image can apply to forest area classification because of clustering in Homogeneous forest type structure. Third, for grading evaluation in forest fire damaged area, if data fusion of established classification method, GLCM texture extraction concept and wavelet transformation technique effectively applied forest areas (also other areas), will obtain high accuracy result.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.97-102
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• 2013

Objective: The aim of this study was to develop an automated computer-aided diagnostic system for diagnosis of thyroid cancer pattern in fine needle aspiration cytology (FNAC) microscopic images with high degree of sensitivity and specificity using statistical texture features and a Support Vector Machine classifier (SVM). Materials and Methods: A training set of 40 benign and 40 malignant FNAC images and a testing set of 10 benign and 20 malignant FNAC images were used to perform the diagnosis of thyroid cancer. Initially, segmentation of region of interest (ROI) was performed by region-based morphology segmentation. The developed diagnostic system utilized statistical texture features derived from the segmented images using a Gabor filter bank at various wavelengths and angles. Finally, the SVM was used as a machine learning algorithm to identify benign and malignant states of thyroid nodules. Results: The SVMachieved a diagnostic accuracy of 96.7% with sensitivity and specificity of 95% and 100%, respectively, at a wavelength of 4 and an angle of 45. Conclusion: The results show that the diagnosis of thyroid cancer in FNAC images can be effectively performed using statistical texture information derived with Gabor filters in association with an SVM.