• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.77-85
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• 2015

The finger language is the part of the sign language, which is a language system that expresses vowels and consonants with hand gestures. Korean finger language has 31 gestures and each of them needs a lot of learning models for accurate recognition. If there exist mass learning models, it spends a lot of time to search. So a real-time awareness system concentrates on how to reduce search spaces. For solving these problems, this paper suggest a hierarchy HMM structure that reduces the exploration space effectively without decreasing recognition rate. The Korean finger language is divided into 3 categories according to the direction of a wrist, and a model can be searched within these categories. Pre-classification can discern a similar finger Korean language. And it makes a search space to be managed effectively. Therefore the proposed method can be applied on the real-time recognition system. Experimental results demonstrate that the proposed method can reduce the time about three times than general HMM recognition method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.133-140
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• 2011

Recently, Web applications, such as Stock Image and Image Library, are developed to provide the integrated management for user's images. Image hash techniques are used for the image registration, management and retrieval as the identifier and many researches have been performed to raise the hash performance. This paper proposes GLOCAL image hashing method utilizing the hierarchical histogram which based on histogram bin population method. So far, many researches have proven that image hashing techniques based on histogram are robust image processing and geometrical attack. We modified existing image hashing method developed by our research team. The main idea is that it makes more fluent hash string if we have histogram bin of specific length as shown in the body of paper. Finally, we can raise the magnitude of hash string within same context or feature and strengthen the robustness of hash.

• The Journal of the Korea Contents Association
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• v.6 no.1
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• pp.31-40
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• 2006

In this paper, we propose a gait recognition method based on gait silhouette sequences. Features of gait are affected by the variation of gait direction. Therefore, we synthesize silhouettes to canonical form by using planar homography in order to reduce the effect of the variation of gait direction. The planar homography is estimated with only the information which exist within the gait sequences without complicate operations such as camera calibration. Even though gait silhouettes are generated from an individual person, fragments beyond common characteristics exist because of errors caused by inaccuracy of background subtraction algorithm. In this paper, we use the Principal Component Analysis to analyze the deviated characteristics of each individual person. PCA used in this paper, however, is not same as the traditional strategy used in pattern classification. We use PCA as a criterion to analyze the amount of deviation from common characteristic. Experimental results show that the proposed method is robust to the variation of gait direction and improves separability of test-data groups.

• Journal of Digital Contents Society
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• v.15 no.6
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• pp.751-761
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• 2014

Color deficient people do not have sufficient discernment for the colors with low saturation and brightness and at the same time express their negative emotions regarding emotion distortion. The purpose of recovering the distortion of the vision which is the basis for emotion is to increase positive emotions rather than negative ones that those with color vision deficiency feel when they experience digital culture contents. Contrast increases saturation and brightness by differing the direction of their conversion and by doing so, delivers emotion distortion such as dynamic vs. static and vivid vs. somber that the original images intend to convey to those with color vision deficiency by reducing such a contrast. In this respect, this study proposes a contrast-based color conversion method to convert saturation and brightness in the zone of color conversion and identifies if this method can reduce emotion distortion by using color conversion simulation and user test.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.1 no.1
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• pp.21-28
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• 2007

In most of hearing aids, amplification algorithms are used to compensate hearing loss, noise and feedback reduction algorithms are used and to increase the perception of speeches contrast enhancement algorithms are used. However, acoustic masking effect is occurred between formants if contrast is enhanced excessively. To confirm the masking effect in speeches, the experiment are composed of 6 tests; test pure tone test, speech reception test, word recognition test, pure tone masking test, formant pure tone masking test and speech masking test, and for objective evaluation, LLR is introduced. As a result of normal hearing subjects and hearing impaired subjects, more making is occurred in hearing impaired subjects than normal hearing subjects when using pure tone, and in the speech masking test, speech reception is also lower in hearing impaired subjects than in normal hearing subjects. This means that acoustic masking effect rather than distortion influences speech perception. So it is required to check the characteristics of masking effect before wearing a hearing aid and to apply this characteristics to fitting curve.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.235-245
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• 2012

Logistic discrimination is an useful statistical technique for quantitative analysis of financial service industry. Especially it is not only easy to be implemented, but also has good classification rate. Generalized additive model is useful for credit scoring since it has the same advantages of logistic discrimination as well as accounting ability for the nonlinear effects of the explanatory variables. It may, however, need too many additive terms in the model when the number of explanatory variables is very large and there may exist dependencies among the variables. Mixtures of factor analyzers can be used for dimension reduction of high-dimensional feature. This study proposes to use the low-dimensional factor scores of mixtures of factor analyzers as the new features in the generalized additive model. Its application is demonstrated in the classification of some real credit scoring data. The comparison of correct classification rates of competing techniques shows the superiority of the generalized additive model using factor scores.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1113-1121
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• 2019

In this paper, we propose the face anti-spoofing method based on combination of luminance and chrominance with convolutional neural networks. The proposed method extracts luminance and chrominance features independently from live and fake faces by using stacked convolutional neural networks and auxiliary networks. Unlike previous methods, an attention module has been adopted to adaptively combine extracted features instead of simply concatenating them. In addition, we propose a new loss function, called the contrast loss, to learn the classifier more efficiently. Specifically, the contrast loss improves the discriminative power of the features by maximizing the distance of the inter-class features while minimizing that of the intra-class features. Experimental results demonstrate that our method achieves the significant improvement for face anti-spoofing compared to existing methods.

• Journal of the Korean Society for Nondestructive Testing
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• v.24 no.1
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• pp.1-7
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• 2004

The angular dependence (or profile) of backscattered ultrasound was measured for steel specimens with a range of surface roughness, $1{\sim}71{\mu}m$. Backscattering profiles at or near the Rayleigh angle still showed roughness dependence while the assessment of surface roughness via normal profile became impossible due to the paint layer masking the roughness. The peak amplitude directly radiated at the Rayleigh angle was proportional to the surface roughness, while the averaged peak amplitude radiated from the backward propagating Rayleigh wave, produced by reflection at a corner, was inversely proportional. In the painted specimens, the linearity of direct backward radiation with the roughness was observed even at the roughness of less than three hundredths of a wavelength, and the abnormal multiple bark reflection caused by periodic roughness disappeared.

• Korean Journal of Community Nutrition
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• v.4 no.1
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• pp.95-102
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• 1999

This study used questionnaires to investigate the safety awareness for imported foods by 365 male and female adults in Taejon. The results of the study were as follow : By factor analysis, the subjects' behaviors and awareness of the imported food was grouped into 3 factors such as 'health and quality factor', 'purchasing factor' and 'contamination factor'. 'Health and quality factor' and 'purchasing factor' were not recognized negatively by the subjects, moreover' contamination factor' was recognized very highly. The subjects' concern and worry about the imported food was also very high. The marital status, education level, nutriton knowledge adn recognition level of contamination by pesticides and heavy metals of foods partially affected the recognitio level of imported foods. The major selection criteria of imported food were distribution period(36.3%), price(28.8%) and purchasing experience(17.3%). The imported food mean discrimination score was 8.4±3.1 out of 13. The worst discriminatio score was red pepper. The subjects' experiences with imported foods selection affected the most instead of education level or nutrition knowledge. The higher discrimination score group more negatively recognized imported food and contamination recognition level was higher whereas the lowerdiscrimination score group more positively recognized the purchasing frequency and with to buy more easily. But both groups desired to reinforce contamination control. The better discrimination score of imported food pooring recognized sanitation concerns(p<0.05), quality(p<0.05), cooking convenience(p<0.01), desire for more variety(p<0.05), and the higher contamination recognition level(p<0.05) and desire to reinforce contamination control(p<0.01).

• Korean Journal of Remote Sensing
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• v.15 no.3
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• pp.183-194
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• 1999

The Brightness, color and texture included in a multispectral satellite data are used as important factors to analyze and to apply the image data for a proper use. One of the most significant process in the satellite data analysis using texture or color information is to extract features effectively expressing the information of original image. It was described in this paper that six features were introduced to extract useful features from the analysis of the satellite data, and also a classification network using the back-propagation neural network was constructed to evaluate the classification ability of each vector feature in SPOT imagery. The vector features were adopted from the training set selection for the interesting region, and applied to the classification process. The classification results showed that each vector feature contained many merits and demerits depending on each vector's characteristics, and each vector had compatible classification ability. Therefore, it is expected that the color and texture features are effectively used not only in the classification process of satellite imagery, but in various image classification and application fields.