• Korea Science and Art Forum
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• v.27
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• pp.101-114
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• 2017

Based on the relationship between urban public space, urban lighting and the sense of place, this paper aims to analyze the lighting environment types with the sense of place and their characteristics. First, with the theory study as the research foundation, it extracts six spatial factors of public space lighting design and then analyzes 12 relevant cases on the basis. Finally, it divides the 12 cases into four types, Basic types, Storytelling, Interactive and Multi-Media and analyzes the core design factor and characteristics of various types. The results show that: first, functionality, sustainability and aesthetics are the basic factors to realize the urban public space lighting places. Second, the six cases of "Storytelling" show that the theme of specific areas, namely the exploration of "story" is conducive for lighting design to form clear and definite environment recognition. Third, for "Interactive" and "Multi-Media", the intervention of new media technology and new lighting way has made the wide expansion of urban lighting design connotation and extension. The research results show that strengthening the urban location performance by the lighting design could improve the city image, which provides the basis for the development of urban public space lighting design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3092-3107
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• 2019

Visible-infrared image fusion is a process of synthesizing an infrared image and a visible image into a fused image. This process synthesizes the complementary advantages of both images. The infrared image is able to capture a target object in dark or foggy environments. However, the utility of the infrared image is hindered by the blurry appearance of objects. On the other hand, the visible image clearly shows an object under normal lighting conditions, but it is not ideal in dark or foggy environments. In this paper, we propose a multi-guided filter and a real-time image fusion method. The proposed multi-guided filter is a modification of the guided filter for multiple guidance images. Using this filter, we propose a real-time image fusion method. The speed of the proposed fusion method is much faster than that of conventional image fusion methods. In an experiment, we compare the proposed method and the conventional methods in terms of quantity, quality, fusing speed, and flickering artifacts. The proposed method synthesizes 57.93 frames per second for an image size of $320{\times}270$. Based on our experiments, we confirmed that the proposed method is able to perform real-time processing. In addition, the proposed method synthesizes flicker-free video.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.3
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• pp.132-140
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• 2007

The quality of the camera image is worse than that of the scanner image because of lighting variation and inaccurate focus. This paper proposes a binarization method for camera-based document recognition, which is tolerant to low-quality camera images. Based on an existing method reported to be effective in previous evaluations, we enhanced the adaptability to the image with a low contrast due to low intensity and inaccurate focus. Furthermore, applying an additional small-size window in the binarization process, it is effective to extract the fine detail of character structure, which is often degraded by conventional methods. In experiments, we applied the proposed method as well as other methods to a document recognizer and compared the performance for many cm images. The result showed the proposed method is effective for recognition of document images captured by the camera.

• Journal of the Korea Computer Graphics Society
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• v.26 no.3
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• pp.87-97
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• 2020

In this paper, we propose a novel neural relighting that infers a relighted rendering image based on the user-guided specular highlight map. The proposed network utilizes a pre-trained neural renderer as a backbone network learned from the rendered image of a 3D scene with various lighting conditions. We jointly optimize a 3D light position and its associated relighted image by back-propagation, so that the difference between the base image and the relighted image is similar to the user-guided specular highlight map. The proposed method has the advantage of being able to explicitly infer the 3D lighting position, while providing the artists' preferred 2D screen-space interface. The performance of the proposed network was measured under the conditions that can establish ground truths, and the average error rate of light position estimations is 0.11, with the normalized 3D scene size.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.55 no.4
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• pp.167-175
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• 2006

This paper presents a method to segment semiconductor wafer ID on poor quality images. The method is based on multiple templates and normalized gray-level correlation (NGC) method. If the lighting condition is not so good and hence, we can not control the image quality, target image to be inspected presents poor quality ID and it is not easy to identify and then recognize the ID characters. Conventional several method to segment the interesting ID regions fails on the bad quality images. In this paper, we propose a multiple template method, which uses combinational relation of multiple templates from model templates to match several characters of the inspection images. To find out the optimal solution of multiple template model in ID regions, we introduce newly-developed snake algorithm. Experimental results using images from real FA environment are presented.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.6
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• pp.468-476
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• 2002

The confidence of information from image processing depends on the original image quality. Enhancing the confidence by an algorithm has an essential limitation. Especially, road images are exposed to lots of noisy sources, which makes image processing difficult. We, in this paper, propose a FNN (fuzzy-neural network) capable oi deciding the quality of a road image prior to extracting lane-related information. According to the decision by the FNN, road images are classified into good or bad to extract lane-related information. A CDF (cumulative distribution function), a function of edge histogram, is utilized to construct input parameters of the FNN, it is based on the fact that the shape of the CDF and the image quality has large correlation. Input pattern vector to the FNN consists of ten parameters in which nine parameters are from the CDF and the other one is from intensity distribution of raw image. Correlation analysis shows that each parameter represents the image quality well. According to the experimental results, the proposed FNN system was quite successful. We carried out simulations with real images taken by various lighting and weather conditions and achieved about 99% successful decision-making.

• ETRI Journal
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• v.31 no.4
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• pp.429-437
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• 2009

This paper proposes a novel technique for 3D scene relighting with interactive viewpoint changes. The proposed technique is based on a deep framebuffer framework for fast relighting computation which adopts image-based techniques to provide arbitrary view-changing. In the preprocessing stage, the shading parameters required for the surface shaders, such as surface color, normal, depth, ambient/diffuse/specular coefficients, and roughness, are cached into multiple deep framebuffers generated by several caching cameras which are created in an automatic manner. When the user designs the lighting setup, the relighting renderer builds a map to connect a screen pixel for the current rendering camera to the corresponding deep framebuffer pixel and then computes illumination at each pixel with the cache values taken from the deep framebuffers. All the relighting computations except the deep framebuffer pre-computation are carried out at interactive rates by the GPU.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.36.4-36
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• 2001

A robust and reliable path recognition system is one necessary component for the autonomous navigation of a mobile robot to help determining its current position in its navigation map. This paper describes a computer visual path-recognition system using on-board video camera as vision-based driving assistance for an autonomous navigation mobile robot. The common problem for a visual system is that its reliability was often influenced by different lighting conditions. Here, two different image processing methods for the path detection were developed to reduce the effect of the luminance: one is based on the RGB color model and features of the path, another is based on the HSV color model in the absence of luminance.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.812-815
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• 2022

Images displayed on a digital devices under the sunlight are generally perceived to be darker than the original images, which leads to a decrease in visibility. For better visibility, global luminance compensation or tone mapping adaptive to ambient lighting is required. However, the existing methods have limitations in chrominance compensation and are difficult to use in real world due to their heavy computational cost. To solve these problems, this paper propose a piece-wise linear curves (PLECs)-based image enhancement method to improve both luminance and chrominance. At this time, PLECs are regressed through deep learning and implemented in the form of a lookup table to real-time operation. Experimental results show that the proposed method has better visibility compared to the original image with low computational cost.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.862-866
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• 2004

Non-intrusive methods based on active remote IR illumination for eye tracking is important for many applications of vision-based man-machine interaction. One problem that has plagued those methods is their sensitivity to lighting condition change. This tends to significantly limit their scope of application. In this paper, we present a new real-time eye detection and tracking methodology that works under variable and realistic lighting conditions. Based on combining the bright-pupil effect resulted from IR light and the conventional appearance-based object recognition technique, our method can robustly track eyes when the pupils are not very bright due to significant external illumination interferences. The appearance model is incorporated in both eyes detection and tracking via the use of support vector machine and the mean shift tracking. Additional improvement is achieved from modifying the image acquisition apparatus including the illuminator and the camera.