• Journal of the Korean Society of Costume
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• v.59 no.2
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• pp.87-100
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• 2009

This study examines black images as 'the other' in history and aims to analyze images of black female fashion models which have been changed in modern society, particularly in $21^{st}$ century post-modern world. Black images, established historically as illustrated on the paintings in $19^{th}$ century, were disseminated in $20^{th}$ century throughout the world especially by way of TV and movies as several typical images such as 'Coon' the clown as the object of entertainment, 'Buck' wild and resistant black rascal, and 'Mammy' obedient and fat black woman servant. The result of image analysis of black female fashion models, can be summarized as following five images. The first is the image of 'powerful'. Black female models frequently represent healthy image which reflects black people's excellence in sports and also the traditional Image of black skin color as strength. The second is the image of 'sexy'. They are adored as having perfect ideal body shape. They show off their sex appeal with their body. The third image is 'multicultural'. Black models represent cultures besides the western. The fourth is the image of 'fantastic'. In contrast to the real, resonable things, black female models represent wild, fancy, ghost things. The fifth is the image of 'racial discrimination' By arranging them in contrast to whites, a metaphoric image of racial discrimination can be displayed. The result shows that tome of racial images still remain on the other way.

• Journal of Sericultural and Entomological Science
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• v.35 no.2
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• pp.105-113
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• 1993

To produce F1 hybrid of silkworm sex discrimination has to be followed at the pupal stage by sexual organ. However it requires a lot of labour and may bring about a wrong classification. In these regards, this study has been implemented to find out an effective measure for the pupal sex discrimination by use of variation of cocoon weight and image analysis of cocoon. As a result, it was found that in case of the pupal weight the percentage of a wrong classification fell on 0.3% and in case of single cocoon weight 0.4%. The discrimination rate was 99% in the weight variables of cocoon but analysis by single cocoon weight and cocoon shape variables, it was 98.7%. Efficiency of discrimination was increased by 2.7% as compared to variable of single cocoon weight. The minimum cocoon sampling size may be 15 cocoons sexual-wise.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.77-82
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• 2021

There are three types of urinalysis: physical test, chemical test, and microscopic test. Among these, the chemical urinalysis is an easily accessible method of the general public to compare the chemical reaction of urinalysis strip with a standard colorimetric table by sight or purchase the portable urinalysis machine separately. Currently, with the popularization of smartphone, research on the urinalysis service using smartphone is increasing. The urinalysis screening application is one of the urinalysis services using a smartphone. However, the RGB values of the urinalysis pad taken by the urinalysis screening application have large deviations due to the effect of lighting. Deviation of RGB value debases the accuracy of urinalysis discrimination. Therefore, in this paper, the accuracy of urinaylsis pad image discrimination is improved through CNN after classifying urinalysis strips taken by the urinalysis screening application based on smartphone by urinalysis pad items. Urinalysis strip was taken from various backgrounds to generate CNN image, and urinalysis discrimination was analyzed using the ResNet-50 CNN model.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.10
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• pp.58-71
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• 1999

When the same image is displayed in many different devices, the reproduced colors are not same due to the differences in the gamut between devices. Therefore, many gamut mapping method were proposed to solve this problem. In this paper, color discrimination enhancement gamut mapping method using color distribution rearrangement is proposed to reduce the unnecessary distortions by compression mapping and to minimize the decrease of color discrimination by clipping method. The proposed method constructs color distribution, the 3-dimension array of input image's colors. if the maximum of color distribution is within the boundary of printer gamut. the colors are mapped to the same colors. Otherwise, out-of-gamut colors are compressed into the printer gamut with minimum distortion. Consequently, the printer output image was highly consistent with the corresponding monitor image and had an enhanced color discrimination in region where high chroma varied linearly.

• Journal of Biosystems Engineering
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• v.35 no.2
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• pp.138-145
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• 2010

An on-line algorithm that discriminates brown rice kernels on their echelon feeder using color image processing is presented for quality inspection. A rapid color image segmentation algorithm based on Bayesian clustering method was developed by means of the look-up table which was made from the significant clusters selected by experts. A robust estimation method was presented to improve the stability of color clusters. Discriminant analysis of color distributions was employed to distinguish nine types of brown rice kernels. Discrimination accuracies of the on-line discrimination algorithm were ranged from 72% to 85% for the sound, cracked, green-transparent and green-opaque, greater than 93% for colored, red, and unhulled, about 92% for white-opaque and 67% for chalky, respectively.

• Journal of Biomedical Engineering Research
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• v.15 no.4
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• pp.419-427
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• 1994

A new method of digital image analysis technique for discrimination of cancer cell was presented in this paper. The object image was the Thyroid Gland cells image that was diagnosed as normal and abnormal (two types of abnormal : follicular neoplastic cell, and papillary neoplastic cell), respectively. By using the proposed region segmentation algorithm, the cells were segmented into nucleus. The 16 feature parameters were used to calculate the features of each nucleus. As a consequence of using dominant feature parameters method proposed in this paper, discrimination rate of 91.11 % was obtained for Thyroid Gland cells.

• Journal of Biosystems Engineering
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• v.37 no.6
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• pp.411-419
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• 2012

Purpose: Nondestructive evaluation of seed viability is a highly demanded technique in the seed industry. In this study, hyperspectral imaging system was used for discrimination of viable and non-viable radish seeds. Method: The spectral data with the range from 400 to 1000 nm measured by hyperspectral reflectance imaging system were used. A calibration and a test models were developed by partial least square discrimination analysis (PLS-DA) for classification of viable and non-viable radish seeds. Either each data set of visible (400~750 nm) and NIR (750~1000 nm) spectra and the spectra of the combined spectral ranges were used for developing models. Results: The discrimination accuracy of calibration was 84% for visible range and 76.3% for NIR range. The discrimination accuracy of test was 84.2% for visible range and 75.8% for NIR range. The discrimination accuracies of calibration and test with full range were 92.2% and 92.5%, respectively. The resultant images based on the optimal PLS-DA model showed high performance for the discrimination of the nonviable seeds from the viable seeds with the accuracy of 95%. Conclusions: The results showed that hyperspectral reflectance imaging has good potential for discriminating nonviable radish seeds from massive amounts of viable seeds.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.171-180
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• 2013

Generally, when we apply zernike moments value for matching, we can use those moments value obtained from projecting image information under circumscribed circle to zernike basis function. However, the problem is that the power of discrimination can be reduced because hand images include lots of overlapped information due to its special characteristic. On the other hand, when distinguishing hand poses, information in specific area of image information except for overlapped information can increase the power of discrimination. In this paper, in order to solve problems like those, we design R3 ring mask by combining image obtained from R2 ring mask, which can weight information of the power of discrimination and image obtained from R1 ring mask, which eliminate the overlapped information. The moments which are obtained by R3 ring mask decrease operational time by reducing dimension through principle component analysis. In order to confirm the superiority of the suggested method, we conducted some experiments by comparing our method to other method using seven different hand poses.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.5
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• pp.518-525
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• 2012

In this study, the feasibility of hyperspectral reflectance imaging technique was investigated for the discrimination of viable and non-viable lettuce seeds. The spectral data of hyperspectral reflectance images with the spectral range between 750 nm and 1000 nm were used to develop PLS-DA model for the classification of viable and non-viable lettuce seeds. The discrimination accuracy of the calibration set was 81.6% and that of the test set was 81.2%. The image analysis method was developed to construct the discriminant images of non-viable seeds with the developed PLS-DA model. The discrimination accuracy obtained from the resultant image were 91%, which showed the feasibility of hyperspectral reflectance imaging technique for the mass discrimination of non-viable lettuce seeds from viable ones.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.125-137
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• 2003

In eastern countries stamps have been used more commonly than signatures when approving contracts and documents. Unlike finger prints, stamp images do not share similar patterns to each other and the resolution of stamp images is determined by the input status such as pressure under which stamps are put. This paper discusses the development of a system for recognizing stamp images of Korean or Chinese characters. Recognition of stamp images consists of several steps: acquisition of stamp images from an input device, digitization, contrast stretching, noise removal, and matching. We tested the system on 50 stamp images (20 stamp images of Korean characters, 20 images of Chinese characters, and 10 similar images). There was little difference in discrimination rate between the stamp images of Korean character and those of Chinese characters. 46 stamps images out of 50 were successfully recognized, resulting in 92% discrimination rate. Orientation and pressure under which stamps are put played an important role in determining discrimination rate. Automated stamp image recognition can be made more practical and useful by extending the types of stamp images to ellipses and rectangles and by improving the discrimination rate.