• Journal of the Optical Society of Korea
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• v.19 no.5
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• pp.456-466
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• 2015

We investigated an anti-aliasing (AA) filter for digital camera photography by which the excessively high-frequency components of the image signal are suppressed to avoid the aliasing effect. Our optomechanical AA filter was implemented by applying rapid relative motions to the imaging sensor. By the engineered motion blur of the mechanical dithers, the effective point-spread function (PSF) of the imaging system could be tailored to reject the unwanted high-frequency components of the image. For optimal operations, we developed a spiral filter motion protocol that could produce a Gaussian-like PSF. We experimentally demonstrated that our AA filter provides an improved filtering characteristic with a better compromise of the rejection performance and the signal loss. We also found that the pass band characteristic can be enhanced further by a color-differential acquisition mode. Our filter scheme provides a useful method of digital photography for low-error image measurements as well as for ordinary photographic applications where annoying $moir{\acute{e}}$ patterns must be suppressed efficiently.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.215-218
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• 2002

The edges of an image hold much of the information in that image. The edges tell where objects are, their shape and size, and something about their texture. An edge is where the intensity of an image moves from a low value to a high value. We introduce the edge detection using the differential operator with Sobel operator and describe a nonparametric Wilcoxon test based on statistical hypothesis testing for the detection of edges. This paper proposes an efficient edge detection using Van der Waerden's statistic in original and noisy images. We use the threshold determined by specifying significance level a and an edge-height parameter. Comparison with our statistical test and Sobel operator shows that Van der Waerden method perform more effectively in both noisy and noise-free images.

• Journal of the Korea Fashion and Costume Design Association
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• v.2 no.2
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• pp.155-171
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• 2000

This study is to measure and evaluate the sensibility image for textile pattern design based on the generation. Ten patterns classified by a practical survey on the market are presented. A questionnaire has 14 sensibility related words scaled by 7 point semantic differential method. The practical research is performed for 200 women screened by sensibility test for individual character analysis based on the generation. Each subject is answered by a face-to-face interview method to improve survey's accuracy, For statistical test about differences in treatment means, SAS package is used and analyzed through ANOVA, significance probability and mean, In summary, this paper has proposed the sensibility image scale for apparel pattern design to satisfy individual sensibility, The results of this study can be effectively applied to develop textile pattern design based on human sensibility.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3077-3079
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• 1999

A visual servoing method has been proposed based on disturbance observer to eliminate the effect of the off-diagonal component of image feature Jacobian, since performance indices such as measurement sensitivity of visual features, sensitivity of the control to noise and controllability could be improved when an image feature Jacobian was given as a block diagonal matrix. In this paper, experimental results of disturbance observer-based visual servoing are discussed where Samsung FARAMAN-ASl 6-axis industrial robot manipulator is employed. Also, the feature saturator is proposed to stabilized the disturbance observer loop by saturating the differential changes of the image features.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.930-932
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• 2003

For this study we used a CCD video camera to capture the pavement image information via the computer. During investigation processing, the CCD video camera captured 10${\sim}$30 images per second. If the vehicle velocity is too fast, the collected images will be duplicated and if the velocity is too slow there will be a gapped between images. Therefore, in order to control the efficiency of the image grabber we should add accessory tools such as the Differential Global Positioning System (DGPS) and odometer. Furthermore, Kalman Filtering can also solve these problems. After the CCD video camera captured the pavement images, we used the Least-Squares method to eliminate images of gradation which have non-uniform surfaces due to the illumination at night. The Fuzzy Entropy method calculates images of threshold segments and creates binary images. Finally, the Object Labeling algorithm finds objects that are cracks or noises from the binary image based on volume pixels of the object. We used these algorithms and tested them, also providing some discussion and suggestions.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.87-89
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• 2018

We proposed an improved reliable SVD-based watermarking scheme resistant to geometric attacks while having high fidelity with no false-positive problem. Principal components of a watermark image are embedded into singular values of LL, LH, HL, and HH sub-bands of a transformed cover image by RDWT(redundant discrete wavelet transform) with optimal scale factors. Each scale factor is generated by trading-off fidelity and robustness using Differential Evolution (DE) algorithm. Zernike Moment (ZM) is used to estimate the geometric distortion and to correct the watermarked image before extracting watermark. The proposed scheme improves fidelity and robustness of existing reliable SVD based watermarking schemes while resisting to geometric attacks.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.3
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• pp.104-113
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• 2000

In this study, we propose facial image recognition based on wavelet transform and neural network. This algorithm is proposed by following processes. First, two gray level images is captured in constant illumination and, after removing input image noise using a gaussian filter, differential image is obtained between background and face input image, and this image has a process of erosion and dilation. Second, a mask is made from dilation image and background and facial image is divided by projecting the mask into face input image Then, characteristic area of square shape that consists of eyes, a nose, a mouth, eyebrows and cheeks is detected by searching the edge of divided face image. Finally, after characteristic vectors are extracted from performing discrete wavelet transform(DWT) of this characteristic area and is normalized, normalized vectors become neural network input vectors. And recognition processing is performed based on neural network learning. Simulation results show recognition rate of 100 % about learned image and 92% about unlearned image.

• Korean Journal of Social Welfare
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• v.59 no.1
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• pp.171-197
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• 2007

This study attempts to explore and describe the public's image on social welfare professionals in the comparison with other helping professionals. Using a sample (n=1,156) collected from high school students, college students, and citizens, this study comparatively examines the public's image on five helping professionals such as social welfare professionals, psychiatrists, clinical psychologists, nurses, and pastoral counselors. In measuring the public's image, this study uses a semantic differential scale that is composed of 16 pairs of adjective words. In overall, among five helping professionals, social welfare professionals is the most positively recognized; thus, its total score is the highest. By using correspondence analysis, social welfare professionals belong to the second quadrant that includes "practical" and "comfortable". As have discussed in the previous research, however, the analysis reveals that social welfare professionals' expertise is not highly evaluated. On the other hand, ANOVA shows that unlike statistically significant differences between social welfare professionals and other helping professionals, there is no statistically significant difference between social welfare professionals and clinical psychologists. Finally, MANOVA shows that except for gender social demographic variables do not make any differences in the public's image on social welfare professionals. In conclusion, this study discusses diverse directions and measures to strengthen social welfare professionals' competencies including expertise and promote the public's image social welfare professionals.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.132-132
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• 2017

Plants, including Platycodon grandiflorum have been used globally across varied cultures as a safe natural source of medicines. From time immemorial, humans have relied on plants that could meet their basic necessities such as food, shelter, fuel and health. This study was executed to profile proteins from the hormone induced diploid and tetraploid roots using high throughput proteome approach. Two dimensional gels stained with CBB, a total of 64 differential expressed proteins were identified from the diploid root using image analysis by Progenesis SameSpot software. Out of total differential expressed spots, 20 differential expressed protein spots ( ${\geq}1.5-fold$) were analyzed using LTQ-FTICR MS whereas a total of 13 protein spots were up regulated and 7 protein spots were down-regulated. However, in the case of tetraploid root, a total of 78 differential expressed proteins were identified from tetraploid root of which a total of 28 differential expressed protein spots (${\geq}1.5-fold$) were analyzed by mass spectrometry whereas a total of 16 protein spots were up regulated and a total of 12 protein spots were down-regulated. However, proteins identified using iProClass databases revealed that the identified proteins from the explants were mainly associated with the nucleic acid binding, oxidoreductase activity, transporter activity and isomers activity. The exclusive protein profile may provide insight clues for better understanding the characteristics of protein function and its metabolic activity that can help for the development of the nutritional and breeding aspects of this economically important medicinal plant.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.123-123
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• 2017

In spite of the potential medicinal significance and a wide range of pharmacologic properties of Platycodon grandiflorum, the molecular mechanism of its roots is still unknown. The present study was conducted to profile proteins from 3, 4 and 5 months aged diploid and tetraploid roots of Platycodon grandiflorum using high throughput proteome approach. Two-dimensional gels stained with CBB, a total of 68 differential expressed proteins were identified from the diploid root out of 767 protein spots using image analysis by Progenesis SameSpot software. Out of total differential expressed spots, 29 differential expressed protein spots (${\geq}2-fold$) were analyzed using LTQ-FTICR MS whereas a total of 24 protein spots were up-regulated and 5 protein spots were down-regulated. On the contrary, in the case of tetraploid root, a total of 86 differential expressed proteins were identified from tetraploid root out of 1033 protein spots of which a total of 39 differential expressed protein spots (${\geq}2-fold$) were analyzed using LTQ-FTICR MS whereas a total of 21 protein spots were up-regulated and a total of 18 protein spots were down-regulated. It was revealed that the identified proteins from the explants were mainly associated with the nucleotide binding, oxidoreductase activity, transferase activity. Taken together, the identified proteins may be helpful to identify key candidate proteins for genetic improvement of plants.