• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.10
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• pp.14-22
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• 2011

The artificial lights to be introduced for the plant factories is requiring the artificial light resources with minimizing the energy consumption to reduce the greenhouse gases which is a major cause of global warming, and maximizing the efficiency in photosynthesis effect light-wave range, in which the plants can be greatly grown and developed, and having the signal light-wave range for forming the light types. the best growing and developing environment for the plants has recently realized with utilizing the LED(Lighting Emitting Diode) lamps, as a environment-friendly green lamps, which can elevating the light efficiency with using only the specific light wave range. In this study, to provide the necessary lights for the full artificial light type of the plant factory, the following research/study and experiments has been conducting. experiments of the spectrum for each light sources, and LED, The intensity of illumination, Irradiance, Photosynthesis Photon Flux Density.

• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1649-1657
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• 2008

In this paper, to overcome the failure of binarization for the characters suffered from low contrast and non-uniform illumination in license plate character recognition system, we improved the binarization method by combining local thresholding with global thresholding and edge detection. Firstly, apply the local thresholding method to locate the characters in the license plate image and then get the threshold value for the character based on edge detector. This method solves the problem of local low contrast and non-uniform illumination. Finally, back-propagation Neural Network is selected as a powerful tool to perform the recognition process. The results of the experiments i1lustrate that the proposed binarization method works well and the selected classifier saves the processing time. Besides, the character recognition system performed better recognition accuracy 95.7%, and the recognition speed is controlled within 0.3 seconds.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.256-261
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• 1999

Global vegetation change is one of major global concerns. Remote sensing images provide an efficient and useful data source to estimate global vegetation covers, and a number of methods have been proposed to estimate them. Among them, the NDVI is one of the most popular indices, and it is_easy to calculate with simple image computing. However, this index is very much affected by the radiometric environment of sensing such as atmospheric conditions and the sun illumination angle. Therefore, it is not appropriate to apply the NDVI to investigate seasonal changes. This paper discusses these problems and proposes an alternative index, MODVI(Modified Vegetation Index), that is less affected by radiometric environment changes. An experiment was conducted to compare these two indices using temporal Landsat TM sub-scenes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.815-823
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• 2004

A hue-based attention operator and a combinational integral projection function(CIPF) are proposed to extract the normalized regions of face and facial features robustly against illumination variation. The face candidate regions are efficiently detected by using skin color filter, and the eyes are located accurately nil robustly against illumination variation by applying the proposed hue- and symmetry-based attention operator to the face candidate regions. And the faces are confirmed by verifying the eyes with the color-based eye variance filter. The proposed CIPF, which combines the weighted hue and intensity, is applied to detect the accurate vertical locations of the eyebrows and the mouth under illumination variations and the existence of mustache. The global face and its local feature regions are exactly located and normalized based on these accurate geometrical information. Experimental results on the AR face database［8］ show that the proposed eye detection method yields better detection rate by about 39.3% than the conventional gray GST-based method. As a result, the normalized facial features can be extracted robustly and consistently based on the exact eye location under illumination variations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.935-944
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• 2013

In this paper, a new illumination compensation algorithm by segmentation with depth information is proposed to improve the coding efficiency of multi-view images. In the proposed algorithm, a reference image is first segmented into several layers where each layer is composed of objects with a similar depth value. Then we separate objects from each other even in the same layer by labeling each separate region in the layered image. Then, the labeled reference depth image is converted to the position of the distortion image view by using 3D warping algorithm. Finally, we apply an illumination compensation algorithm to each of matched regions in the converted reference view and distorted view. The occlusion regions that occur by 3D warping are also compensated by a global compensation method. Through experimental results, we are able to confirm that the proposed algorithm has better performance to improve coding efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2075-2092
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• 2017

Person re-identification is to match pedestrians observed from non-overlapping camera views. It has important applications in video surveillance such as person retrieval, person tracking, and activity analysis. However, it is a very challenging problem due to illumination, pose and viewpoint variations between non-overlapping camera views. In this work, we propose a viewpoint invariant method for matching pedestrian images using orientation of pedestrian. First, the proposed method divides a pedestrian image into patches and assigns angle to a patch using the orientation of the pedestrian under the assumption that a person body has the cylindrical shape. The difference between angles are then used to compute the similarity between patches. We applied the proposed method to real-time global multi-object tracking across multiple disjoint cameras with non-overlapping field of views. Re-identification algorithm makes global trajectories by connecting local trajectories obtained by different local trackers. The effectiveness of the viewpoint invariant method for person re-identification was validated on the VIPeR dataset. In addition, we demonstrated the effectiveness of the proposed approach for the inter-camera multiple object tracking on the MCT dataset with ground truth data for local tracking.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.19-21
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• 2004

In many cases, human's visual recognition depends on contextual information. We need to use effective feature information for performing vigorous place recognition to illumination, noise, etc. In the existing cases that use edge and color, etc., visual recognition doesn't cope effectively with real environment. To solve this problem, using natural marker, we improve the efficiency of place recognition.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.991-994
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• 2002

Photon mapping is an efficient global illumination technique for realistic image synthesis that has been developed in computer graphics. In this paper, an adaptive photon mapping in the use of automatic differentiation is proposed. Since the automatic differentiation is used when photons emit from the light sources through the scene, we can check the variation of surrounding shape. Therefore, we can decrease the number of photons and generate an image in relatively low computational cost.

• Proceedings of the Optical Society of Korea Conference
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• 2008.07a
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• pp.393-394
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• 2008

컴퓨터 그래픽의 분야에서 Global illumination을 계산하는 과정은 우선 광선 추적 기법을 기반으로 한다. 가장 늦게 소개되어 사용자 층이 늘어나고 있는 photon mapping 기법도 scene rendering을 수행하기 이전에 광선 추적을 이용하여 photon의 공간적 분포를 미리 계산하는 과정을 활용한다. 본 고(稿)에서는 광학용으로 사용되는 SW를 scene rendering에 활용할 수 있는 가능성을 검증하였다.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.2
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• pp.101-108
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• 2015

In this paper, a robust traffic light detection method is proposed by using vision sensor and DGPS(Difference Global Positioning System). The conventional vision-based detection methods are very sensitive to illumination change, for instance, low visibility at night time or highly reflection by bright light. To solve these limitations in visual sensor, DGPS is incorporated to determine the location and shape of traffic lights which are available from traffic light database. Furthermore the geometric relationship between traffic light and vision sensor is used to locate the traffic light in the image by using DGPS information. The empirical results show that the proposed method improves by 51% in detection rate for night time with marginal improvement in daytime environment.