• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.137-144
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• 2009

Understanding lane markings in a live video captured from a moving vehicle is essential to build services for intelligent vehicles such as LDWS(Lane Departure Warning Systems), unmanned vehicles, video-based car navigation systems. In this paper, we present a novel approach to recognize the color of lane markings and the lane number that he/she is driving on. More specifically, we present a background-color removal approach to understand the color of lane markings for various illumination conditions, such as backlight, sunset, and so on. In addition, we present a probabilistic network approach to decide the lane number. According to our experimental results, the proposed idea shows promising results to detect lane number in a various illumination conditions and road environments.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.157-165
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• 2011

It is challenging to detect foreground objects when background includes an illumination variation, shadow or structural variation due to its motion. Basically pixel-based background models including codebook-based modeling suffer from statistical randomness of each pixel. This paper proposes an algorithm that incorporates Markov random field model into pixel-based background modeling to achieve more accurate foreground detection. Under the assumptions the distance between the pixel on the input imaging and the corresponding background model and the difference between the scene estimates of the spatio-temporally neighboring pixels are exponentially distributed, a recursive approach for estimating the MRF regularizing parameters is proposed. The proposed method alternates between estimating the parameters with the intermediate foreground detection and estimating the foreground detection with the estimated parameters, after computing it with random initial parameters. Extensive experiment is conducted with several videos recorded both indoors and outdoors to compare the proposed method with the standard codebook-based algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.366-369
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• 2005

Background subtraction is mainly used for the real-time extraction and tracking of moving objects from image sequences. In the outdoor environment, there are many changeable factor such as gradually changing illumination, swaying trees and suddenly moving objects, which are to be considered for the adaptive processing. Normally, GMM(Gaussian Mixture Model) is used to subtract the background adaptively considering the various changes in the scenes, and the adaptive GMMs improving the real-time performance were worked. This paper, for on-line background subtraction, applied the improved adaptive GMM, which uses the small constant for learning rate ${\alpha}$ and is not able to speedily adapt the suddenly movement of objects, So, this paper proposed and evaluated the dynamic control method of ${\alpha}$ using the adaptive selection of the number of component distributions and the global variances of pixel values.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.329-338
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• 2003

Object tracking in a real time image is one of Interesting subjects in computer vision and many practical application fields past couple of years. But sometimes existing systems cannot find object by recognize background noise as object. This paper proposes a method of object detection and tracking using adaptive background image in real time. To detect object which does not influenced by illumination and remove noise in background image, this system generates adaptive background image by real time background image updating. This system detects object using the difference between background image and input image from camera. After setting up MBR(minimum bounding rectangle) using the internal point of detected object, the system tracks object through this MBR. In addition, this paper evaluates the test result about performance of proposed method as compared with existing tracking algorithm.

• Archives of Plastic Surgery
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• v.41 no.2
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• pp.126-132
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• 2014

Background Extensive degloving injuries of the extremities usually result in necrosis of the flap, necessitating comprehensive skin grafting. Provided there is a sufficient tool to evaluate flap viability, full-thickness skin can be used from a nonviable avulsed flap. We used a Wood's lamp to determine the viability of avulsed flaps in the operation field after intravenous injection of fluorescein dye. Methods We experienced 13 cases during 16 months. Fifteen minutes after the intravenous injection of fluorescein dye, the avulsed skin flaps were examined and non-fluorescent areas were marked under Wood's lamp illumination. The marked area was defatted for full-thickness skin grafting. The fluorescent areas were sutured directly without tension. The non-fluorescent areas were covered by defatted skin. Several days later, there was soft tissue necrosis within the flap area. We measured necrotic area and revised the flap. Results Among all the cases, necrotic area was 21.3% of the total avulsed area. However, if we exclude three cases, one of a carelessly managed patient and two cases of the flaps were inappropriately applied, good results were obtained, with a necrotic area of only 8.4%. Eight patients needed split-thickness skin grafts, and heel pad reconstruction was performed with free flap. Conclusions A full-thickness skin graft from an avulsed flap is a good method for addressing aesthetic concerns without producing donor site morbidity. Fluorescein dye is a useful, simple, and cost-effective tool for evaluating flap viability. Avulsed flap injuries can be managed well with Wood's lamp illumination and a full-thickness skin graft.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.223-232
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• 2014

The feasibility of a virtual colored overlay is based on constraints of computer and user preference and it is evaluated for people with Scotopic Sensitivity Syndrome. We draw ${\alpha}$ and chromaticities of virtual colored overlay which will be implemented on IT devices by measuring optical characteristics of 2 representative film overlays and simulating them. We analyzed the influence of two illuminating conditions on the virtual colored overlay. We find that it is possible to get the multiple combinations of alpha and source RGB values to match a chromaticity which is presented in CIE-Luv color space under ideal white condition of display, a user can select one among them with respect to clarity and comfort. Under 100 lx difference of illumination conditions, the changes of chromaticities are negligible, but luminances are increased $37.8cd/m^2$ average(std 2.006) at high illumination condition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.630-636
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• 2020

This study reviewed camouflage techniques to reduce the visual detect-ability of aircraft. Visual camouflage can be defined as the process of making objects less visible. Aircraft visual camouflage delays detection of the aircraft position, speed, and flight direction. Multi-tone and counter-shaded schemes are generally adopted as camouflage patterns for close-air-support aircraft and air-superiority aircraft, respectively. Another study showed that the monotone scheme is also efficient when the hue and brightness of the camouflage color are controlled correctly. Active camouflage techniques for aircraft have been studied to increase the camouflage effectiveness. In particular, counter-illumination techniques using electroluminescence devices can minimize the difference in brightness between the aircraft and sky background. Active camouflage techniques are expected to enhance the survivability of low-altitude UAVs, which are vulnerable to visual detection.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.72-80
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• 2016

There are various methods of developing latent fingerprints from evidence found at crime scenes. Crime scene investigators should choose appropriate techniques among them depending on the conditions of the evidences. In this study, we compared the three methods using forensic light sources to develop latent fingerprints on multi-colored surfaces. We selected the various samples according to color, shape and texture of the surfaces and developed the latent fingerprints using fluorescent powder, IR(Infrared) photography and Episcopic Co-axial Illumination. Fluorescent powder was highly effective on all surfaces. IR photography was also effective, but only on the not dark surfaces. Episcopic Co-axial Illumination was effective only on the flat and polished surfaces. Although fluorescent powder was fine regardless of the characteristics of the surfaces, IR photography was better on certain surfaces.

• Journal of Korea Multimedia Society
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• v.16 no.9
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• pp.1031-1043
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• 2013

Extracting hand region from images is the first part in the process to recognize hand posture and gesture interaction. Therefore, a good segmenting method is important because it determines the overall performance of hand recognition systems. Conventional hand segmentation researches were prone to changing illumination conditions or limited to the ability to detect multiple people. In this paper, we propose a robust technique based on the fusion of skin-color data and depth information for hand segmentation process. The proposed algorithm uses skin-color data to localize accurate seed location for region-growing from a complicated background. Based on the seed location, our algorithm adjusts each detected blob to fill up the hole region. A region-growing algorithm is applied to the adjusted blob boundary at the detected depth image to obtain a robust hand region against illumination effects. Also, the resulting hand region is used to train our skin-model adaptively which further reduces the effects of changing illumination. We conducted experiments to compare our results with conventional techniques which validates the robustness of the proposed algorithm and in addition we show our method works well even in a counter light condition.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.93-96
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• 2001

In this paper, we present a vision algorithm and method for input image improvement and preprocessing of dented and raised characters on the sidewall of tires. we define optical condition between reflect coefficient and reflectance by the physical vector calculate. On the contrary this work will recognize the engraved characters using the computer vision technique. Tire input images have all most same grey levels between the characters and backgrounds. The reflectance is little from a tire surface. therefore, it's very difficult segment the characters from the background. Moreover, one side of the character string is raised and the other is dented. So, the captured images are varied with the angle of camera and illumination. For optimum input images, the angle between camera and illumination was found out to be with in 90。 .In addition, We used complex filtering with low-pass and high-pass band filters to improve input images, for clear input images. Finally we define equation reflect coefficient and reflectance. By doing this, we obtained good images of tires for pattern recognition.