• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.41-50
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• 2022

In this paper, a method to directly calculate the major elements of skin color such as melanin and hemoglobin from the RGB signal of the camera is proposed. The main elements of skin color typically measure spectral reflectance using specific equipment, and reconfigure the values at some wavelengths of the measured light. The values calculated by this method include such things as melanin index and erythema index, and require special equipment such as a spectral reflectance measuring device or a multi-spectral camera. It is difficult to find a direct calculation method for such component elements from a general digital camera, and a method of indirectly calculating the concentration of melanin and hemoglobin using independent component analysis has been proposed. This method targets a region of a certain RGB image, extracts characteristic vectors of melanin and hemoglobin, and calculates the concentration in a manner similar to that of Principal Component Analysis. The disadvantage of this method is that it is difficult to directly calculate the pixel unit because a group of pixels in a certain area is used as an input, and since the extracted feature vector is implemented by an optimization method, it tends to be calculated with a different value each time it is executed. The final calculation is determined in the form of an image representing the components of melanin and hemoglobin by converting it back to the RGB coordinate system without using the feature vector itself. In order to improve the disadvantages of this method, the proposed method is to calculate the component values of melanin and hemoglobin in a feature space rather than an RGB coordinate system using a feature vector, and calculate the spectral reflectance corresponding to the skin color using a general digital camera. Methods and methods of calculating detailed components constituting skin pigments such as melanin, oxidized hemoglobin, deoxidized hemoglobin, and carotenoid using spectral reflectance. The proposed method does not require special equipment such as a spectral reflectance measuring device or a multi-spectral camera, and unlike the existing method, direct calculation of the pixel unit is possible, and the same characteristics can be obtained even in repeated execution. The standard diviation of density for melanin and hemoglobin of proposed method was 15% compared to conventional and therefore gives 6 times stable.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.8
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• pp.1162-1169
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• 2016

A new method based on accelerated solvent extraction (ASE) combined with response surface methodology (RSM) has been developed for optimization of the extraction of ginsenoside [Rb1, Rg1, and Rg3(20S)], total phenolics, and benzopyrene in red ginseng. The RSM method, based on a five level and two variable central composite design, was employed to obtain the optimal combination of extraction conditions. In brief, ginsenosides Rb1, Rg1, and Rg3(20S) and total phenolics with undetectable benzopyrene were optimally extracted with 50% ethanol as an extraction solvent, extraction temperature of $158^{\circ}C$, extraction time of 20 min, extraction pressure of 2,500 psi, flush volume of 60%, and one extraction cycle. The contents of ginsenosides and total phenolics in red ginseng extracted by ASE under optimum conditions were significantly higher than those extracted by sonication and reflux extraction.

• The Journal of Engineering Geology
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• v.3 no.3
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• pp.241-252
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• 1993

Lead bas been found in the groundwater in Door County, Wiscorsin, with temporally and spatially irregular distribution in concentration. Correlation coeffidents were calculated among lead indicators in groundwater(frequency of lead detections, mean and maximum concentration of lead detections) and seven independent variables(stucture and geographic factors of wells, hydrogeological factors at lead-arsenate mixing sites and the level of soil contamination) which are possibly related to the lead level in groundwater. The significance of relationships was determined statistically by a t-test at the 90% confidence level, and indicated that the spatially located lead-arsenate mixing sites provided the lead in groundwater in the study area. A total of 112 groundwater samples were collected from 5 house wells with previous lead detects. Lead was detected in partides on ifiter papers with $0.45{\;}\mu\textrm{m}$ pore size, but not in filtrates. The result of chemical analysis for lead indicates that lead is associated with partides in groundwater in Door County. Subsequently, the irregular distribution of lead in the county results from the transport of particulate lead along the advective groundwater movement through the preferential pathways sucn as vertical and bedding-plane joints.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05a
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• pp.325-328
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• 2003

문장분석은 문장의 의미를 파악하기 위한 작업이다. 문장분석에는 문장 구성성분에 종합적인 정보를 필요로 한다. 문장분석을 위해서는 다양한 언어학적 도구와 자원이 필요하다. 가용 도구와 자원은 대부분 독립적으로 개발 축적된 것들이다. 이러한 도구와 자원을 이용하여 문장분석 정보들을 단계적으로 관리하고 처리하기에는 어려움이 있다. 이를 위해 본 논문에서는 문장분석용 통합 사용자 인터페이스 ISAAC를 개선하여 구문분석의 성공률과 그 정보의 상호보완성을 높이고자 하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.555-562
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• 2012

This paper presents a hybrid method for improving the recognition performance, which is based on the nonlinear histogram equalization, features extraction, and statistical correlation of images. The nonlinear histogram equalization based on a logistic function is applied to adaptively improve the quality by adjusting the brightness of the image according to its intensity level frequency. The statistical correlation that is measured by the normalized cross-correlation(NCC) coefficient, is applied to rapidly and accurately express the similarity between the images. The local features based on independent component analysis(ICA) that is used to calculate the NCC, is also applied to statistically measure the correct similarity in each images. The proposed method has been applied to the problem for recognizing the 30-face images of 40*50 pixels. The experimental results show that the proposed method has a superior recognition performances to the method without performing the preprocessing, or the methods of conventional and adaptively modified histogram equalization, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.192-197
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• 2020

Multivariate processes, such as large scale power plants or chemical processes are operated in very hazardous environment, which can lead to significant human and material losses if a fault occurs. On-line monitoring technology, therefore, is essential to detect system faults. In this paper, the ICA-based fault detection method is conducted using three different multivariate process data. Fault detection procedure based on ICA is divided into off-line and on-line processes. The off-line process determines a threshold for fault detection by using the obtained dataset when the system is normal. And the on-line process computes statistics of query vectors measured in real-time. The fault is detected by comparing computed statistics and previously defined threshold. For comparison, the PCA-based fault detection method is also implemented in this paper. Experimental results show that the ICA-based fault detection method detects the system faults earlier and better than the PCA-based method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.6
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• pp.22-31
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• 2000

In this paper, we propose a method for removing noise components in the feature extraction process for robust speech recognition. This method is based on blind separation using independent component analysis (ICA). Given two noisy speech recordings the algorithm linearly separates speech from the unwanted noise signal. To apply ICA as closely as possible to the feature level for recognition, a new spectral analysis is presented. It modifies the computation of band energies by previously averaging out fast Fourier transform (FFT) points in several divided ranges within one met-scaled band. The simple analysis using sample variances of band energies of speech and noise, and recognition experiments showed its noise robustness. For noisy speech signals recorded in real environments, the proposed method which applies ICA to the new spectral analysis improved the recognition performances to a considerable extent, and was particularly effective for low signal-to-noise ratios (SNRs). This method gives some insights into applying ICA to feature levels and appears useful for robust speech recognition.

• Journal of the Korean Society of Food Science and Nutrition
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• v.35 no.6
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• pp.780-785
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• 2006

The composition analysis of various radish (Rapharnus sativus L.) leaves and the effects of drying condition on the quality characteristics of hot-air dried radish leaves were carried out by a response surface methodology. Independent variables put in drying temperature $(X_1)$ and drying time $(X_2)$, dependent variables put in color, calcium, iron, vitamin, etc. In the proximate composition of radish leaves by varieties, there were no significant differences in the ash, protein, lipid, calcium and iron content of samples, but there were significant differences in the vitamins, chlorophyll and color value of samples. The quality characteristics on dried radish leaves by central composite design, it was significant value on the moisture content, chlorophyll and color value according to drying temperature and drying times. But there were no significant differences in the contents of calcium $(31.41{\sim}35.80\;mg/g,\;dry\;base)$ and iron $(0.21{\sim}0.29\;mg/g\;dry\;base)$. The multiplex regression coefficients analysis were calculated with independent variables $(X_1,\;X_2)$ and dependent variables (moisture, chlorophyll, color value). The calculated coefficient correlations for the each samples were $R^2>0.97$. The effects of drying temperature were greater than drying time in the total chlorophyll content changes of radish leaves. Based on the present study, the optimum drying condition for the lowest color changes and effective reduction of moisture of radish leaves were expected to be $5{\sim}6$ hours at $70^{\circ}C$.

• Journal of the Korean Society of Food Science and Nutrition
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• v.34 no.9
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• pp.1477-1484
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• 2005

The effects of various seasoning components, pH of seasoning solution, heating time and storage temperature were investigated on the color and textural properties of the salted radish root (nanmooji) The effects of individual seasoning components in the salted radish root, additives of polyphosphate (AD3), citric acid (AD5), malic acid (AD2) delayed the color changes and softening more, compared to control soaked in water. On the other hand, additives of potassium sorbate (AD1), succinic acid (AD7), MSG (AD8), saccharin (AD6) accelerated the color changes and softening of the salted radish roots. The effects of pH of seasoning solution($X_1$), and heating time ($X_2$) were central composite design and response surface analysis. R- square represented dependent variables correlated independent variables ($X_1,\;X_2$), showed over 0.8 in the color and area value calculated thickness and firmness of salted radish root. Especially, R- square of 'b' represented 'yellow-green' was 0.899. And the result of crossing analysis of individual independent variables ($X_1,\;X_2$), showed that both independent variables had significant effects on the color and textural changes of the salted radish root. The salted radish root increased its color changes and softening, rapidly at $40^{\circ}C$, compared to the other storage temperatures at most storage periods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.33-42
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• 2005

Identifying color codes needs precise color information of their constituents, and is far from trivial because colors usually suffer severe distortions throughout the entire procedures from printing to acquiring image data. To accomplish accurate identification of colors, we need a reliable segmentation method to separate different color regions from each other, which would enable us to process the whole pixels in the region of a color statistically, instead of a subset of pixels in the region. Color image segmentation can be accomplished by performing edge detection on component image(s). In this paper, we separately detected edges on component images from RGB, HSI, and YIQ color models, and performed mathematical analyses and experiments to find out a pair of component images that provided the best edge image when combined. The best result was obtained by combining Y- and R-component edge images.