• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1999.11a
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• pp.240-246
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• 1999

This parer proposes fuzzy reasoning algorithm for improvement in Zonal Cavity Method that is difficult to calculate average illumination without lighting scope and reflection factor so on. This parer use fuzzy reasoning algorithm for maintainment of the best illumination in spite of some variation those are influenced of room illumination and cut down the difficult to be calculated used Zonal Cavity Method.

• Solar Energy
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• v.11 no.1
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• pp.3-15
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• 1991

In this study global radiation and global illumination are directly measured and diffuse radiation and diffuse illumination measured utilizing semi-circular shadow ring. By analyzing measured radiation data, clear and overcast sky are classified according to the sky classification method used in Mantes, France. Measured illumination data are analyzed and 1) Clear sky illumination on a horizontal surface as a function of solar altitude. 2) Overcast sky illumination on a horizontal surface as a function of solar altitude, 3) Monthly variation of illumination. 4) Cumulative percentage of illumination, 5) Daylight intensity as a function of hours in a typical day, 6) Average number hours per day of illumination above 10 and 20klx are presented as a climatic data for daylighting design for Seoul, Korea.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.7
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• pp.503-506
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• 2013

In this paper, we propose the face recognition method combining the ECSP preprocessing technique which is modified version of previous CS-LBP and the illumination-robust D2D-PCA feature. The performance evaluation of proposed method was carried out using various binary pattern operators and feature extraction algorithms such as well-known PCA and 2D-PCA on the Yale B database. As a results, the proposed method showed the best recognition accuracy compared to different approaches, and we confirmed that the proposed approach is robust to illumination variation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1104-1113
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• 2015

In this paper, we propose Two-Dimensional Robust Face Recognition System Realized with the Aid of Facial Symmetry with Illumination Variation. Preprocessing process is carried out to obtain mirror image which means new image rearranged by using difference between light and shade of right and left face based on a vertical axis of original face image. After image preprocessing, high dimensional image data is transformed to low-dimensional feature data through 2-directional and 2-dimensional Principal Component Analysis (2D)2PCA, which is one of dimensional reduction techniques. Polynomial-based Radial Basis Function Neural Network pattern classifier is used for face recognition. While FCM clustering is applied in the hidden layer, connection weights are defined as a linear polynomial function. In addition, the coefficients of linear function are learned through Weighted Least Square Estimation(WLSE). The Structural as well as parametric factors of the proposed classifier are optimized by using Particle Swarm Optimization(PSO). In the experiment, Yale B data is employed in order to confirm the advantage of the proposed methodology designed in the diverse illumination variation

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.21-28
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• 2006

In a face detection system based on template matching, histogram equalization or log transform is applied to an input image for the intensity normalization and the image improvement. It is known that they are noneffective in improving an image with intensity distortion by illumination variation. In this paper, we propose an efficient image improvement method using a simple regression analysis combined with a bilateral symmetry average for images with intensity distortion by illumination variation. Experimental results show that our method delivers the detection performance better than previous methods and also remarkably reduces the number of face candidates.

• Journal of KIISE
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• v.44 no.3
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• pp.295-305
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• 2017

Facial appearance is greatly influenced by illumination conditions, and therefore illumination variation is one of the factors that degrades performance of face recognition systems. In this paper, we propose a robust method for face representation under varying illumination conditions, combining non-alpha Weberface (non-alpha WF) and histogram equalization. We propose a two-step method: (1) for a given face image, non-alpha WF, which is not applied a parameter for adjusting the intensity difference between neighboring pixels in WF, is computed; (2) histogram equalization is performed to non-alpha WF, to make a uniform histogram distribution globally and to enhance the contrast. $(2D)^2PCA$ is applied to extract low-dimensional discriminating features from the preprocessed face image. Experimental results on the extended Yale B face database and the CMU PIE face database show that the proposed method yielded better recognition rates than several illumination processing methods as well as the conventional WF, achieving average recognition rates of 93.31% and 97.25%, respectively.

• Journal of Korean Ophthalmic Optics Society
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• v.4 no.2
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• pp.91-96
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• 1999

This study involves the research about relationship between visual charts and illumination. The subjects were both males and females in their teens and twenties. The examination instrument used was a B-VAT II BVS(Mentol) which was produced in the USA, and the illumination used was a low illumination of 100LUX and a high illumination of 1500LUX in the clinical examination room. The results were as follows: 1. Different types of illumination resulted in similar values of visual acuity. 2. In the male teen subjects, the Snellen visual acuity was better than the numerical visual acuity when using low illumination. But the Landolt visual acuity presented similar results when using both low and high illumination. 3. In male subjects in their twenties, the Numerical visual acuity was better than the Landolt and Snellen visual acuity under low illumination. 4. In the female teen subjects, The Snellen visual acuity was better than the Landolt and Numerical visual acuity under low illumination. 5. In the female subjects in their twenties, The Snellen, Landolt and numerical visual acuities were high under low illumination. 6. Different types of illumination resulted in 0.3 or 0.4 variation of visual acuity. 7. The males and females was similar to the visual acuity.

• Agricultural and Biosystems Engineering
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• v.5 no.1
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• pp.5-9
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• 2004

This study was carried out to develop methods of reducing the effect of solar illumination on pixel gray-levels of machine vision for agricultural field use. Two kinds of monochrome CCD cameras with manual and auto-iris lenses were used to take pictures within a range of 15 to 120 klux of solar illumination. A camera having more precise automatic control functions gave much better result. Four kinds of indices using pixel gray-level of the $99\%$ white DRS (diffuse reflectance standard) as a reference were tried to compensate pixel gray-levels of an image for variable illumination. Coefficients of variation of the indices within a range of illumination were used as a criterion for comparison. The study concluded that an index of (A+B)/A, where A is gray-level of the $99\%$ DRS and B is gray-level of the tested material, gave the best consistency in the range of solar illumination.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.157-164
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• 2017

In this research, the overlapped illumination model was used for designing a freeform LED lens with a uniform illuminance distribution on its illuminating plane, and their performances and tolerances were compared. And, the illuminations on a illumination plane was measures for change with average illuminance and illuminance uniformity. As a result of the tolerance analysis about z-axis direction change, thickness change in lens and tilt change of light emission and characteristic change in LED source, overlapped model and divergent illumination model are similar to the performance about Z-axis direction change of light emission in LED source. but the uniformity illumination value in this overlapped model is more remarkably value than it in divergent illumination model about thickness change in LED lens. Also, even though the lens based on a divergent illumination model showed good performance compare to the lens based on an overlapped illumination model, the latter was less the deviation to variation of LED beam radiation ability.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.10
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• pp.604-614
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• 2005

Color segmentation takes great attentions since a color is an effective and robust visual cue for characterizing one object from other objects. Color segmentation is, however, suffered from color variation induced from irregular illumination changes. This paper proposes a reliable color modeling approach in HSI (Hue-Saturation-Intensity) rotor space considering intensity information by adopting B-spline curve fitting to make a mathematical model for statistical characteristics of a color with respect to brightness. It is based on the fact that color distribution of a single-colored object is not invariant with respect to brightness variations even in HS (Hue-Saturation) plane. The proposed approach is applied for the segmentation of human skin areas successfully under various illumination conditions.