• Journal of the Korean Institute of Rural Architecture
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• v.25 no.4
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• pp.1-8
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• 2023

This study is meaningful in figuring out how much the Korean people's awareness of hanok has increased even though interest in hanok has also increased due to the Korean Wave craze. Therefore, with respect to the exterior of hanok, which is visually recognized first, the level of experts and ordinary people is grasped through a semantic discrimination scale, and the degree of visual recognition is to be investigated centering on the color image of hanok buildings. This is the process of thinking about how the Korean image should be reflected in the design, and we want to suggest the direction that modern hanok should go. The study compared and analyzed the difference in visual color based on the elevation of the hanok using a 7-point and 5-point scale method for the general public and experts, and utilized the IRI adjective vocabulary scale and the color matching image scale to construct new hanoks with insufficient differences in appearance and shape. It can be applied to design and image preservation and construction of existing hanok.

• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.225-236
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• 2013

3D contents could cause unique 3D visual fatigue. Screen disparity, image blurring, and crosstalk are known to be the three major factors responsible for the fatigue. Among these, screen disparity and image blurring are content factors, that is, one can directly manipulate contents themselves to handle visual fatigue caused by these two factors. On the other hand, because crosstalk is closely tied to physical characteristics of 3D display, it is difficult or even impossible to reduce crosstalk-driven visual fatigue unless one replaces 3D display itself (for example, from active to passive display). However, the effects of crosstalk on 3D visual fatigue depends on visual stimulus features (that is, contents), and thus it is possible to manipulate stimulus features in order to handle visual fatigue caused by crosstalk. Hence, this research tested the effects of visual stimulus features on crosstalk (which then causes 3D visual fatigue). Using relative depth discrimination task, we tested the effects of stimulus-background contrast, background texture density, and screen disparity on the degree of perceived crosstalk. The results showed that crosstalk decreases with presence of background texture and with less degree of screen disparity.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.14 no.1
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• pp.81-94
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• 2003

Objectives：Developmental reading disorder is a condition which manifests significant developmenttal delay in reading ability or persistent errors. About 3-7% of school-age children have this condition. The purpose of the present study was to validate the diagnostic values of Word/Nonword Reading Test and Letter-Symbol Discrimination Task for the purpose of overcoming the caveats of Basic Learning Skills Test. Methods：Sixty-three reading-disordered patients(mean age 10.48 years old) and sex, age-matched 77 normal children(mean age 10.33 years old) were selected by clinical evaluation and DSM-IV criteria. Reading I and II of Basic Learning Skills Test, Word/Nonword Reading Test, and Letter-Symbol Discrimination Task were carried out to them. Word/Nonword Reading Test：One hundred usual highfrequency words and one hundred meaningless nonwords were presented to the subjects within 1.2 and 2.4 seconds, respectively. Through these results, automatized phonological processing ability and conscious letter-sound matching ability were estimated. Letter-Symbol Discrimination Task：mirror image letters which reading-disordered patients are apt to confuse were used. Reliability, concurrent validity, construct validity, and discriminant validity tests were conducted. Results：Word/Nonword Reading Test：the reliability(alpha) was 0.96, and concurrent validity with Basic Learning Skills test was 0.94. The patients with developmental reading disorders differed significantly from normal children in Word/Nonword Reading Test performances. Through discriminant analysis, 83.0% of original cases were correctly classified by this test. Letter-Symbol Discrimination Task：the reliability(alpha) was 0.86, and concurrent validity with Basic Learning Skills test was 0.86. There were significant differences in scores between the patients and normal children. Factor analysis revealed that this test were composed of saccadic mirror image processing, global accuracy, mirror image processing deficit, static image processing, global vigilance deficit, and inattention-impulsivity factors. By discriminant analysis, 87.3% of the patients and normal children were correctly classified. Conclusion：The patients with developmental reading disorders had deficits in automatized visuallexical route, morpheme-phoneme conversion mechanism, and visual information processing. These deficits were reliably and validly evaluated by Word/Nonword Reading Test and Letter-Symbol Discrimination Task.

• Communications of Mathematical Education
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• v.30 no.4
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• pp.453-468
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• 2016

This study is a result of experiment to recognize geometric and spacial conceptions for early childhood. This researcher had built up Mandala figures which was an intermediary between consciousness and unconsciousness, and then have studied about early childhood's geometric and spatial concepts by using Mandala figures. In this paper, authors have studied fractal art activities of early childhood as a follow-up study, since the structure of fractal art is similar to Mandala. As a result, three years old young children have significant correlation in four areas(figure perception, visual discrimination, position-in space perception and visual memory), but five years old young children have significant in three areas(figure perception, position-in space perception and visual memory). For five years old group, there is some difference between boys and girls, also they had described for their art activities like real models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1824-1845
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• 2016

The GMM is a conventional approach which has been recently applied in many face recognition studies. However, the question about how to deal with illumination changes while ensuring high performance is still a challenge, especially with real-world databases. In this paper, we propose a Visual Observation Confidence (VOC) measure for robust face recognition for illumination changes. Our VOC value is a combined confidence value of three measurements: Flatness Measure (FM), Centrality Measure (CM), and Illumination Normality Measure (IM). While FM measures the discrimination ability of one face, IM represents the degree of illumination impact on that face. In addition, we introduce CM as a centrality measure to help FM to reduce some of the errors from unnecessary areas such as the hair, neck or background. The VOC then accompanies the feature vectors in the EM process to estimate the optimal models by modified-GMM training. In the experiments, we introduce a real-world database, called KoFace, besides applying some public databases such as the Yale and the ORL database. The KoFace database is composed of 106 face subjects under diverse illumination effects including shadows and highlights. The results show that our proposed approach gives a higher Face Recognition Rate (FRR) than the GMM baseline for indoor and outdoor datasets in the real-world KoFace database (94% and 85%, respectively) and in ORL, Yale databases (97% and 100% respectively).

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2875-2878
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• 2003

In this paper, we propose an EEG-based mental state prediction method during a mental tasks. In the experimental task, a subject goes through the process of responding to visual stimulus, understanding the given problem, controlling hand motions, and hitting a key. Considering the subject's varying brain activities, we model subjects' mental states with defining selection time. EEG signals from four subjects were recorded while they performed three mental tasks. Feature vectors defined by these representations were classified with a standard, feed-forward neural network trained via the error back-propagation algorithm. We expect that the proposed detection method can be a basic technology for brain-computer interface by combining with left/right hand movement or cognitive decision discrimination methods.

• Journal of the Optical Society of Korea
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• v.18 no.6
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• pp.809-817
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• 2014

The loss in contrast-discrimination ability of the human visual system under high ambient illumination level can cause image quality degradation in mobile phones. In this paper, we propose a perceived contrast compensation method by processing the original displayed image. With consideration that the perceived contrast significantly varies across the image, this method extracts the local band contrast from the original image; it then compensates these contrast components to counteract the perceived contrast degradation. Experimental results demonstrate that this method can maintain most contrast details even in high ambient illumination levels.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.459-460
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• 2001

In this paper, we analyze algorithms for diagnosing of VEP(visual evoked potential) signal. We used wavelet transform for the preprocessing of VEP signal data and back propagation neural network for the pattern recognition. We used several wavelets to study their effects and efficiency in the preprocessing of VEP. The diagnosis system led to good results. We obtained the noise reduced and compressed signal with the wavelet transform of the training VEP signal. So it is possible to train the neural network faster and exact diagnosis processing is possible in the neural network. From the experimental results, we know that the discrimination ability of the neural network is changed by the type of basis vector and the proposed system is good to the diagnosis of VEP.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.399-400
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• 2007

This paper proposes an regional analytic approach in image data space for radiographic image. Image is segmented into four regions, such as background, thickness, weld area and tube area, due to directional properties. Each region has its own gray level distribution, contrast range and noise property, originated from X-ray project mechanism and electric control system itself. Projection incorrectness and noise influence included on imaging quality is analyzed functionally and statistically. The experimental results shows not only segmental effects, but also visual edge evaluation.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1030-1032
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• 2003

This study a imed to analyze the effect of combined optical and radar image for the land cover classification in coastal region. The study area, Gyeonggi Bay area has one of the largest tidal ranges and has frequent land cover changes due to the several reclamations and rather intensive land uses. Ten land cover types were classified using several datasets of combining Landsat ETM+ and RADARSAT imagery. The synergic effects of the merged datasets were analyzed by both visual interpretation and an ordinary supervised classification. The merged optical and SAR datasets provided better discrimination among the land cover classes in the coastal area. The overall classification accuracy of merged datasets was improved to 86.5% as compared to 78% accuracy of using ETM+ only.