• New & Renewable Energy
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• v.5 no.4
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• pp.34-37
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• 2009

Using six SMD(surface mount device) type AlGaAs/GaAs single junction solar cells connected in series, a power source was fabricated for a white GaN LED. The electrical properties of the power source was measured and analyzed under one sun (100mW/$cm^2$) and various indoor light (300 - 900 lux) conditions. Under 600 lux indoor light condition, output power was 17.06 ${\mu}W$ and it was 30.75 ${\mu}W$ under 900 lux indoor light condition. Using the fabricated solar cell power supply, we have turned on the white GaN LED. It was worked well under 15 ${\mu}W$(at 480 lux) power supplied from solar cell array. This kind of solar cell power supply can be used as a power source for ubiquitous sensor network (USN).

• Journal of Korea Multimedia Society
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• v.21 no.11
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• pp.1244-1253
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• 2018

The color of traffic light is sensitive to various illumination conditions. Especially it loses the hue information when oversaturation happens on the lighting area. This paper proposes a traffic light recognition method robust to these illumination variations. The method consists of two steps of traffic light detection and recognition. It just uses the intensity and saturation in the first step of traffic light detection. It delays the use of hue information until it reaches to the second step of recognizing the signal of traffic light. We utilized a deep learning technique in the second step. We designed a deep convolutional neural network(DCNN) which is composed of three convolutional networks and two fully connected networks. 12 video clips were used to evaluate the performance of the proposed method. Experimental results show the performance of traffic light detection reporting the precision of 93.9%, the recall of 91.6%, and the recognition accuracy of 89.4%. Considering that the maximum distance between the camera and traffic lights is 70m, the results shows that the proposed method is effective.

• Journal of KIBIM
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• v.13 no.2
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• pp.29-36
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• 2023

This study explores the potential of utilizing video-based data analysis and machine learning techniques to estimate the number of occupants within a building. The research methodology involves developing a sophisticated counting system capable of detecting and tracking individuals' entry and exit patterns. The proposed method demonstrates promising results in various scenarios; however, it also identifies the need for improvements in camera performance and external environmental conditions, such as lighting. The study emphasizes the significance of incorporating machine learning in architectural and urban planning applications, offering valuable insights for the field. In conclusion, the research calls for further investigation to address the limitations and enhance the system's accuracy, ultimately contributing to the development of a more robust and reliable solution for building occupancy estimation.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.5
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• pp.785-792
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• 2023

Because hyperspectral imaging provides detailed spectral information across a broad range of wavelengths, it can be utilized in numerous applications, including environmental monitoring, food quality inspection, medical diagnosis, material identification, art authentication, and crime scene analysis. However, hyperspectral images often contain various types of distortions due to the environmental conditions during image acquisition, which necessitates the proper removal of these distortions through a data preprocessing process. In this study, a preprocessing method was investigated to effectively correct the distortion caused by artificial light sources used in indoor hyperspectral imaging. For this purpose, a halogen-tungsten artificial light source was installed indoors, and hyperspectral images were acquired. The acquired images were then corrected for distortion using a preprocessing that does not require complex auxiliary equipment. After the corrections were made, the results were analyzed. According to the analysis, a statistical transformation technique using mean and standard deviation with reference to a reference signal was found to be the most effective in correcting distortions caused by artificial light sources.

• International Journal of Highway Engineering
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• v.18 no.3
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• pp.127-134
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• 2016

PURPOSES : Low visibility caused by dark surroundings at nighttime affects the likelihood of accidents, and various efforts, such as installing road safety facilities, have been made to reduce accidents at night. Despite these efforts, the nighttime severity index (SI) in Korea was higher than the daytime SI during 2011-2014. This study determined the factors affecting daytime and nighttime accident severity through a discriminant analysis. METHODS : Discriminant analysis. RESULTS : First, drowsiness, lack of attention, and lighting facilities affected both daytime and nighttime accident severity. Accidents were found to be caused by a low ability to recognize the driving conditions and a low obstacle avoidance capability. Second, road conditions and speeding affected only the daytime accident severity. Third, failure to maintain a safe distance significantly affected daytime accident severity and nonsignificantly affected nighttime accident severity. The majority of such accidents were caused by rear-end collisions of vehicles driving in the same direction; given the low relative speed difference in such cases, the shock imparted by the accidents was minimal. CONCLUSIONS : Accidents caused by a failure to maintain a safe distance has lower severity than do accidents caused by other factors.

• Journal of the Korean Solar Energy Society
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• v.30 no.1
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• pp.25-33
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• 2010

Use of daylight in underground space interacts with physiological need for human beings and provides relief from feeling secluded. Light pipe system can deliver natural light into the space where it is needed and can be used as primary or a secondary light source with benefits of energy, productivity and health. To use light pipe system effectively under various conditions, it is important to investigate the effectiveness of light pipe system with reliable monitoring protocol. This paper presents the results of light pipe system performance used in underground parking lot under different sky conditions. Comparisons were made between the illuminance standards of underground parking lot and the monitored data. The results indicated that adequate illuminance level was shown until 4.5m distance from the light pipe under clear sky condition. However, additional lighting device showed be used under overcast sky to meet the proper illuminance level.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.891-894
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• 2017

Lane detection algorithms became a key factor of advance driver assistance system (ADAS), since the rapidly increasing of high-technology in vehicles. However, one common problem of these algorithms is their performance's instability under various illumination conditions. We recognize a feasible complementation between image processing and color science to address the problem of lane marks detection on the road with different lighting conditions. We proposed a novel lane detection algorithm using the attributes of a uniform color space such as $CIEL^*C^*h$ with the implementation of image processing techniques, that lead to positive results. We applied at the final stage Clustering to make more accurate our lane mark estimation. The experimental results show the effectiveness of our method with detection rate of 91.80%. Moreover, the algorithm performs satisfactory with changes in illumination due to our process with lightness ($L^*$) and the color's property on $CIEL^*C^*h$.

• The Journal of Advanced Prosthodontics
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• v.16 no.1
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• pp.48-56
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• 2024

PURPOSE. To evaluate the metameric disparities among monolithic zirconia materials with differing yttrium compositions across various lighting conditions. MATERIALS AND METHODS. Thirty-six square-shaped zirconia samples measuring 10 × 10 × 0.5 mm were prepared from monolithic zirconia materials with three different yttrium contents. A 0.2 mm thick layer of polymerized dual-polymerizable self-adhesive resin cement was created using a silicone mold with the same dimensions as the prepared zirconia specimens. To evaluate metamerism, color measurements were conducted using a spectrophotometer device on a neutral gray background in a color measurement cabinet that offers four different illumination environments. All samples underwent aging by subjecting them to 10000 thermal cycles using a thermal cycle tester. Following thermal aging, color measurements were taken once more, and the data were recorded using the CIE L^*, a^*, b^* color system. Two-way ANOVA and Post-hoc Bonferroni tests were employed to analyze the data. RESULTS. It was observed that there was no statistical difference among the color measurements made in different illumination environments of the monolithic zirconia ceramics used to evaluate metamerism (P > .05). This observation remained consistent both before and after thermal aging. After thermal aging, the color of monolithic zirconia materials exhibited a tendency towards red and yellow hues, accompanied by a decrease in brightness levels. CONCLUSION. It can be stated that different illumination conditions did not affect the metamerism of monolithic zirconia materials, but there was a color change in monolithic zirconia materials after a thermal aging period equivalent to one year.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.77-86
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• 2014

Mobile devices are generally using app images which are artificially designed. Accordingly, this paper presents adjusting device brightness based on app image categorization for enhancing the visibility under various light condition. First, the proposed method performed two prior subjective tests under various lighting conditions for selecting features of app images concerning visibility and for selecting satisfactory range of device brightness for each app image. Then, the relationship between selected features of app image and satisfactory range of device brightness is analyzed. Next, app images are categorized by using two features of average brightness of app image and distribution ratio of advanced colors that are related to satisfaction range of device brightness. Then, optimal device brightness for each category is selected by having the maximum frequency of satisfaction device brightness. Experimental results show that the categorized app images with optimal device brightness have high satisfaction ratio under various light conditions.

• Journal of Internet Computing and Services
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• v.9 no.1
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• pp.171-177
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• 2008

In this paper we compared the performance of interpolation algorithms for Bayer patterned image sensors under the various illumination intensities. As the interpolation algorithms, we used bilinear color interpolation and adaptive fuzzy color interpolation and our experimentation shows that performance of interpolation algorithms depend on the lighting conditions; in low intensity of illumination, bilinear color interpolation with median filter performs best, in high intensity of illumination, adaptive fuzzy color interpolation performs best, and in between bilinear color interpolation performs best. This study suggested an interpolation scheme which applies different interpolation algorithm according to the intensity of the input image, resuting in the better image quality.