• Proceedings of the Plant Resources Society of Korea Conference
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• 2020.12a
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• pp.62-62
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• 2020

Ginseng is a shade-plant cultivated using shading facilities. However, at too low light levels, root growth is poor, and at high light levels, the destruction of chlorophyll reduces the photosynthesis efficiency due to leaf burn and early fall leaves. The ginseng has a lightsaturation point of 12,000~15,000 lux when grown at 15 to 20℃ and 9,500 lux at 25℃. This study was conducted to select the optimal light intensity of 3-year-old ginseng grown in blue-white film plastic house. The seeds were planted in the blue-white film plastic house with different light receiving rate (March 17, 2020). Between April and September, the average air temperature in the house was 20.4-20.7℃. Average soil temperature was 18.3℃-18.5℃. The chemical properties of the test soil was as follows. The pH level was 7.0-7.4, EC was 0.5-0.6 dS/m, OM was at the levels of 33.6-37.7 g/kg, P₂O₅ was 513.0-590.8 mg/kg, slightly higher than the allowable 400 mg/kg. The amount of light intensity, illuminance, and solar radiation in the blue-white film house was increased as the light-receiving rate increased and the amount of light intensity was found to be 9-14% compared to the open field, 8-13% illuminance and 9-14% solar irradiation respectively. The photosynthesis rate was the lowest at 3.1 µmolCO²/m²/s in the 9% light blue-white plastic house and 4.2 and 4.0 µmolCO²/m²/s in the 12% and 14% light blue-white plastic house, respectively. These results generally indicate that the photosynthesis of plants increases with the amount of light, but the ginseng has a lower light saturation point at high temperatures, and the higher the amount of light, the lower the photosynthetic efficiency. The SPAD (chlorophyll content) value decreased as the increase of light-receiving rate, and was the highest at 32.7 in 9% light blue-white plastic house. Ginseng germination started on April 11 and took 13-15 days to germinate. The overall germination rate was 82.9-85.8%. The plant height and length of stem were long in the 9% light-receiving plastic house. The diameter of stem was thick in the 12-14% light-receiving plastic house. In the 12% and 14% light-receiving plastic house, the length and diameter of taproot was long and thick, so the fresh weight of root per plant was 20 g or more, which was heavier than 16.9 g of the 9% light-receiving plastic house. The disease incidence (Alternaria blight, Gray mold and Damping-off etc.) rate were 0.9-2.7%. The incidence of Sclerotinia rot disease was 7.5-8.4%, and root rot was 0-20.0%. The incidence ratio of rusty root ginseng was 34.4-38.7% level, which was an increase from the previous year's 15% level.

• The Transactions of the Korea Information Processing Society
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• v.1 no.2
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• pp.215-224
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• 1994

In this paper, the rotation and size invariant fingerprint recognition using the neural network EART (Extended Adaptive Resonance Theory) is studied ($515{\times}512$) gray level fingerprint images are converted into the binary thinned images based on the adaptive threshold and a thinning algorithm. From these binary thinned images, we extract the ending points and the bifurcation points, which are the most useful critical feature points in the fingerprint images, using the $3{\times}3$ MASK. And we convert the number of these critical points and the interior angles of convex polygon composed of the bifurcation points into the 40*10 critical using the weighted code which is invariant of rotation and size as the input of EART. This system produces very good and efficient results for the rotation and size variations without the restoration of the binary thinned fingerprints.

• Journal of Biosystems Engineering
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• v.37 no.4
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• pp.271-278
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• 2012

Worldwide trends in animal welfare have resulted in an increased interest in individual management of sows housed in groups within hog barns. Estrus detection has been shown to be one of the greatest determinants of sow productivity. Purpose: We conducted this study to develop a method that can automatically detect the estrus state of a sow by selecting optimal texture parameters from images of a sow's pudendum and by optimizing the number of neurons in the hidden layer of an artificial neural network. Methods: Texture parameters were analyzed according to changes in a sow's pudendum in estrus such as mucus secretion and expansion. Of the texture parameters, eight gray level co-occurrence matrix (GLCM) parameters were used for image analysis. The image states were classified into ten grades for each GLCM parameter, and an artificial neural network was formed using the values for each grade as inputs to discriminate the estrus state of sows. The number of hidden layer neurons in the artificial neural network is an important parameter in neural network design. Therefore, we determined the optimal number of hidden layer units using a trial and error method while increasing the number of neurons. Results: Fifteen hidden layers were determined to be optimal for use in the artificial neural network designed in this study. Thirty images of 10 sows were used for learning, and then 30 different images of 10 sows were used for verification. Conclusions: For learning, the back propagation neural network (BPN) algorithm was used to successful estimate six texture parameters (homogeneity, angular second moment, energy, maximum probability, entropy, and GLCM correlation). Based on the verification results, homogeneity was determined to be the most important texture parameter, and resulted in an estrus detection rate of 70%.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.814-818
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• 2004

Off-line handwritten character recognition is in difficulty of incomplete preprocessing because it has not dynamic and timing information besides has various handwriting, extreme overlap of the consonant and vowel and many error image of stroke. Consequently off-line handwritten character recognition needs to study about preprocessing of various methods such as binarization and thinning. This paper considers running time of watershed algorithm and the quality of resulting image as preprocessing For off-line handwritten Korean character recognition. So it proposes application of effective watershed algorithm for segmentation of character region and background region in gray level character image and segmentation function for binarization image and segmentation function for binarization by extracted watershed image. Besides it proposes thinning methods which effectively extracts skeleton through conditional test mask considering running time and quality. of skeleton, estimates efficiency of existing methods and this paper's methods as running time and quality. Watershed image conversion uses prewitt operator for gradient image conversion, extracts local minima considering 8-neighborhood pixel. And methods by using difference of mean value is used in region merging step, Converted watershed image by means of this methods separates effectively character region and background region applying to segmentation function. Average execution time on the previous method was 2.16 second and on this paper method was 1.72 second. We prove that this paper's method removed noise effectively with overlap stroke as compared with the previous method.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.3
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• pp.26-31
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• 1999

In this paper, we propose a facial characteristic detection algorithm based on knowledge and object segmentation method for image communication. In this algorithm, under the condition of the same lumination and distance from the fixed video camera to human face, we capture input images of 256 $\times$ 256 of gray scale 256 level and then remove the noise using the Gaussian filter. Two images are captured with a video camera, One contains the human face; the other contains only background region without including a face. And then we get a differential image between two images. After removing noise of the differential image by eroding End dilating, divide background image into a facial image. We separate eyes, ears, a nose and a mouth after searching the edge component in the facial image. From simulation results, we have verified the efficiency of the Proposed algorithm.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.49-55
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• 2016

In digital forensic images, there is a serious problem that is distributed with various image types. For the problem solution, this paper proposes a classification algorithm of the forensic image types. The proposed algorithm extracts the 21-dim. feature vector with the contrast and energy from GLCM (Gray Level Co-occurrence Matrix), and the entropy of each image type. The classification test of the forensic images is performed with an exhaustive combination of the image types. Through the experiments, TP (True Positive) and FN (False Negative) is detected respectively. While it is confirmed that performed class evaluation of the proposed algorithm is rated as 'Excellent(A)' because of the AUROC (Area Under Receiver Operating Characteristic Curve) is 0.9980 by the sensitivity and the 1-specificity. Also, the minimum average decision error is 0.1349. Also, at the minimum average decision error is 0.0179, the whole forensic image types which are involved then, our classification effectiveness is high.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.80-87
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• 2007

In this paper, we investigate an enhancement method for Western epigraphic images, which is based on local statistics. Image data is partitioned into two regions, background and information. Statistical and functional analyses are proceeded for image modeling. The Western epigraphic images, for the most part, have shown the Gaussian distribution. It is clarified that each region can be differentiated statistically. The local normalization process algorithm is designed on this model. The parameter is extracted and it‘s properties are verified with the size of moving window. The spatial gray-level distribution is modified and regions are differentiated by adjusting parameter and the size of moving window. Local statistics are utilized for realization of the enhancement, so that difference between regions can be enhanced and noise or speckles of region can be smoothed. Experimental results are presented to show the superiority of the proposed algorithm over the conventional methods.

• Journal of IKEEE
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• v.13 no.2
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• pp.224-231
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• 2009

Unsharp masking is a popular image enhancement technique used to sharpen an image appearance in gray images. However, the conventional unsharp making techniques amplify the noise and easily cause overshoot artifacts. Moreover, the unsharp masking tends to introduce color distortion when it is applied to the each color component independently. To solve these problems, we propose a novel unsharp masking technique based on human visual system and vector projection. The proposed algorithm consists of two steps. First, the proposed algorithm controls the level of sharpening by exploiting the characteristics of the human visual system and contrast region. Then the vector projection is applied to remove the color distortion. Experiment results show that our proposed algorithm successfully produces sharpened images that are free of noise and color distortion commonly found in the conventional unsharp masking algorithms.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.23 no.3
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• pp.398-407
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• 1999

In the present image processing technique, the concept of the gradient indicator(GI) has been introduced to find out the depth-of-field in sizing large particles ranging from $30{\mu}m$ to $30{\mu}m$ where using of the concept of the normalized contrast value(VC) is not appropriate. The gradient indicator is defined as the ratio of the local value to the maximum possible value of the gray-level gradient in an image frame. The gradient indicator decreases with the increases of the particle size and the distance from the exact focal plane. A particle is considered to be in focus when the value of the gradient indicator at its image boundary stays above a critical value. This critical gradient indicator($GI_{critical}$) is defined as the maximum gradient indicator($GI_{max}$) subtracted by a constant ${\Delta}GI$ which is to account for the particle-size effect. In the present ca.so, the value of ${\Delta}GI$ was set to 0.28 to keep the standard deviation of the measured particles mostly within 0.1. It was also confirmed that, to find the depth-of-field for small particles(${\leq}30{\mu}m$) with the same measurement accuracy, tho concept of the critical normalized contrast($VC_{critical}$) is applicable with 85% of the maximum normalized contrast value($VC_{max}$). Finally, the depth-of-field was checked for the size range between $10{\mu}m$ and $300{\mu}m$ when the both in-focus criteria ($GI_{critical}$ and $VC_{critical}$) were adopted. The change of the depth-of-field with the particle size shows good linearity in both the VC-applicable and the GI-applicable ranges with a reasonable accuracy.

• The Journal of Advanced Prosthodontics
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• v.12 no.3
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• pp.150-156
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• 2020

PURPOSE. The aim of this study was to evaluate the effect of different surface finishing processes on the color stabilities of lithium disilicate glass-ceramics, zirconia-reinforced lithium silicate ceramics, and resin nanoceramics after artificial ageing. MATERIALS AND METHODS. 216 samples were prepared from 3 different CAD/CAM materials (LAVA Ultimate, IPS e.max CAD, VITA Suprinity) with A1 HT color at a size of 14 × 12 mm and a thickness of 0.5 ± 0.05 mm. Color measurements of the samples were performed with a spectrophotometer using color parameters and CIE Lab color system on a gray backing between baseline color and after 5000 cycles of artificial ageing in 4 stages (i.e. the first measurement before the treatment, the second measurement after polishing, the third measurement after cement application, and the fourth measurement after artificial ageing). The results were evaluated using the Variance analysis and Fisher's LSD test. RESULTS. Resin nanoceramics (LU) exhibited higher color change values than zirconia-reinforced lithium silicate (VS) and lithium disilicate (EC) ceramics after artificial ageing. Manual polishing and glazing resulted in similar color change for LU and VS (P>.05). In the EC group, glazing provided statistically different results as compared to the manual polishing and control groups (P<.05). Among the ceramic groups, color change values of the subgroup, which was treated by glazing, of the zirconia-reinforced lithium silicate (VS) and lithium disilicate (EC) samples were below the clinically acceptable level (ΔE < 3.5). CONCLUSION. The lowest color change for all stages was observed in Vita Suprinity.