• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.78.3-78.3
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• 2019

We develop a novel technique that can constrain the evolutionary track of the epoch of reionization (EoR) by applying the convolutional neural network (CNN) to the 21-cm differential brightness temperature. We use 21cmFAST, a fast semi-numerical cosmological 21-cm signal simulator, to produce mock 21-cm map between z=6-13. We design a CNN architecture that predicts the volume-averaged neutral hydrogen fraction from the given 21-cm map. The estimated neutral fraction has a good agreement with its truth value even after smoothing the 21-cm map with somewhat realistic choices of beam size and the frequency bandwidth of the Square Kilometre Array (SKA). Our technique could be further utilized to denoise the 21-cm map or constrain the properties of the radiation sources.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.66.2-66.2
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• 2020

We propose a deep learning analysis technique with a convolutional neural network (CNN) to predict the evolutionary track of the Epoch of Reionization (EoR) from the 21-cm differential brightness temperature tomography images. We use 21cmFAST, a fast semi-numerical cosmological 21-cm signal simulator, to produce mock 21-cm maps between z = 6 ~ 13. We then apply two observational effects, such as instrumental noise and limit of (spatial and depth) resolution somewhat suitable for realistic choices of the Square Kilometre Array (SKA), into the 21-cm maps. We design our deep learning model with CNN to predict the sliced-averaged neutral hydrogen fraction from the given 21-cm map. The estimated neutral fraction from our CNN model has great agreement with the true value even after coarsely smoothing with broad beam size and frequency bandwidth and heavily covered by noise with narrow beam size and frequency bandwidth. Our results show that the deep learning analyzing method has the potential to reconstruct the EoR history efficiently from the 21-cm tomography surveys in future.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.231-236
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• 2011

The binarization algorithm frequently applies to one part of the preprocessing phase for a variety of image processing techniques such as image recognition and image analysis, etc. So it is important that binarization algorithm is determined by the selection of threshold value for binarization in image processing. The previous algorithms could get the proper threshold value in the case that shows all the difference of brightness between background and object, but if not, they could not get the proper threshold value. In this paper, we propose the efficient fuzzy binarization method which first, segments the brightness range of gray_scale images to 2 intervals to perform car license plate binarization and applies fuzzy member function to each intervals. The experiment for performance evaluation of the proposed binarization algorithm showed that the proposed algorithm generates the more effective threshold value than the previous algorithms in car license plate.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.363-366
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• 2003

We propose the system that automatically adjusts the white balance on display products to a standard value according to several nations. We replace manual or semi-auto method with fully automatic method using windows application program. And we use RS-232C serial interface to communicate PC with display products which we want to adjust white balance. The PC generates patterns for measuring color information and Color Analyzer measures color and brightness. This value is transmitted through RS-232C serial interface to PC. The PC's algorithm analyzes this information and then decides which RGB Gain value is best for optimal white balance. This RGB Gain value is transmitted through RS-232C serial interface to display products. The modified color value is measured again and feed back to PC. This sequence is repeated until optimum white balance is obtained.

• Journal of the Korea Computer Industry Society
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• v.9 no.2
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• pp.69-76
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• 2008

This paper implement an Camcorder NTSC camera autofocus control system on the DSP Board. The information of camera lens control obtain the only brightness simple image processing from the NTSC camcoder camera image. The exact focus makes the exact boundaries. The camera lens control that the increase sum of the useful ingredient values. Useful value obtained experiment value. Also noise is except because a big value of the ingredients so that obtained focus more accurate value.

• Journal of Mushroom
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• v.8 no.2
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• pp.51-58
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• 2010

Total eight different winter mushroom (Flammulina velutipes) strains were characterized by comparisons of fruiting body morphology, hardness and color after growing at different temperature. Although variations depending on the strains were observed, in general, both stipe length and pilus diameter were shorter while pilus thickness was bigger as growing temperatures were decreased. No significant differences in stipe thickness were observed. The ASI4065 and 4151 had the tallest stipe and the ASI4021 had the shortest stipe. The ASI4103 strain had the biggest pilus diameter. The ASI4153 had most thick pilus, while the ASI 4021 had least thick pilus. Also, the ASI4166 had the most thick stipe and the ASI4065 had the most thin stipe. The hardness of white mushrooms were increased by decreasing growth temperatures, while no relationships between the hardness of brown mushrooms. In most strains, stipe were much stronger than pilei and white mushrooms were harder than brown ones. The strain having most strong stipe was ASI4021. Both ASI 4021 and ASI4166 had the most strong pilus. The color of pilus has much lighter than that of stipe. White mushrooms had high brightness value ranging from 70-90, while brown mushrooms showed low brightness value from 30-70. Saturation value was higher in brown mushrooms. Based on our study, it was shown that environmental conditions had some effects on winter mushrooms, but genetic differences among strains were more important factors to determine most characteristics of winter mushrooms.

• Journal of the Korean Society of Tobacco Science
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• v.20 no.2
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• pp.191-197
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• 1998

Discriminant analysis using near infrared spectra derived from Korean Flue-cured(KF) and American Flue-cured(AF), and also Korean Burley(KB) and American Burley(AB) tobacco was done to classify flue-cured and burley tobacco as either grown in Korea or grown in the USA. Samples were scanned in the wavelength of 400 ～ 2500 nm by near infrared analyzer(NIRSystem Co., model 6500). The discrimination equations for flue-cured and burley tobacco were developed using partial least square 2 method in Infrasoft International NIRS 3 software package. KF samples used for the development of the discrimination equations were higher contents of total sugar, crude ash and chlorine, and higher value of leaf density and brightness, but lower contents of nicotine, total nitrogen and ether extracts, and higher value of redness than those of AF samples. KB samples were higher contents of nicotine, crude ash and chlorine, but lower contents of ether extracts and value of brightness than those of AB samples. On 3 dimensional graph drawn with 3 principal component scores calculated with 3 principal component from KF and KB sample spectra, KF sample spectra were significantly different from AF, and also KB sample spectra were significantly different from AB. The discrimination equations of flue-cured and burley were developed with 3 principal component, respectively. The discrimination equations for flue-cured and burley had a standard error of 0.03 and 0.04, and a R2 of 0.88 and 0.84, respectively. The tobacco samples used for the development of discrimination equation were perfectly classified as KF and AF by flue-cured discrimination equation, and also perfectly classified KB and AB by burley discrimination equation, respectively. The correct classification rates of KF and AF samples not used for the development of discrimination equations were 9S % (828 out of 869 samples) and 98 % (98 out of 100 samples) by flue-cured discrimination equations, and KB and AB samples were 94%(345 out of 368 samples) and 100%(42 out of 42 samples) by burley discrimination equations, respectively.

• Journal of the East Asian Society of Dietary Life
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• v.24 no.3
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• pp.383-391
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• 2014

This study was conducted to ascertain the antioxidant properties of Hamcho (Salicornia herbacea L.) and as well as manufacture pettitoes using Hamcho as a natural antioxidant material for diverse applications. The DPPH radical scavenging activities of 25, 50, 100 mg/mL in methanol extracts from Salicornia herbacea L. increased significantly (p<0.05) to 12.8%, 21.6% and 39.1%, respectively. The total phenolic content was $38.58{\pm}4.25{\mu}M$ as tannic acid equivalent for 100 mg/mL of methanol extracts from Hamcho. FRAP value was $448.58{\pm}14.01{\mu}M$ as ascorbic acid equivalent in reducing power. To apply Hamcho to food as a natural antioxidant, pettitoes were prepared with added Hamcho. To manufacture pettitoes added with Hamcho, general quality characteristics of pettitoes added with 0%, 2%, 4% and 6% based on 100 g of pettitoes were determined. In conclusion, mineral components increased according to the added amount of Salicornia herbacea L. Crude protein showed the highest value with 2% added Hamcho. Overall, the addition of Hamcho led to hardening of the meat texture. As a result of measuring color in terms of brightness, redness, and yellowness with chromaticity, the L value (brightness) increased with added amount of Hamcho. There was no significant difference in redness or yellowness. As a result of the sensory evaluation of pettitoes according to addition of Hamcho, the group with 4% added Hamcho showed enhanced overall preference with improved flavor, taste and textural properties.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.101-108
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• 2024

AI-OCR (Artificial Intelligence Optical Character Recognition) combines OCR technology with Artificial Intelligence to overcome limitations that required human intervention. To enhance the performance of AI-OCR, training on diverse data sets is essential. However, the recognition rate declines when image colors have similar brightness levels. To solve this issue, this study employs Homomorphic filtering as a preprocessing step to clearly differentiate color levels, thereby increasing text recognition rates. While Homomorphic filtering is ideal for text extraction because of its ability to adjust the high and low frequency components of an image separately using a gamma value, it has the downside of requiring manual adjustments to the gamma value. This research proposes a range for gamma threshold values based on tests involving image contrast, brightness, and entropy. Experimental results using the proposed range of gamma values in Homomorphic filtering suggest a high likelihood for effective AI-OCR performance.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.41-49
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• 2022

Recently interests on the application of thermal cameras have increased with the advance of image analysis technology. Aside from a simple image acquisition, applications such as digital twin and thermal image management systems have gained popularity. To this end, we studied the effect of emissivity on the DN (Digital Number) value in the process of derivation of a relational expression for converting DN to an actual surface temperature. The DN value is a number representing the spectral band value of the thermal image, and is an important element constituting the thermal image data. However, the DN value is not a temperature value indicating the actual surface temperature, but a brightness value indicating high and low heat as brightness, and has a non-linear relationship with the actual surface temperature. The reliable relationship between DN and the actual surface temperature is critical for a thermal image processing. We tested the relationship between the actual surface temperature and the DN value of the thermal image, and then the radiation adjustment was performed to better estimate actual surface temperatures. As a result, the relation graph between the actual surface temperature and the DN value similarly show linear pattern with the relation graph between the radiation-controlled non-contact thermometer and the DN value. And the non-contact temperature after adjusting the emissivity was closer to the actual surface temperature than before adjusting the emissivity.