• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.727-731
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• 2003

ASTER image has some advantages for classification such as 15 spectral bands and 15m ${\sim}$ 90m spatial resolution. However, in the classification using general remote sensing image, shadow areas are often classified into water area. It is very difficult to divide shadow and water. Because reflectance characteristics of water is similar to characteristics of shadow. Many land cover items are consisted in one pixel which is 15m spatial resolution. Nowadays, very high resolution satellite image (IKONOS, Quick Bird) and Digital Surface Model (DSM) by air borne laser scanner can also be used. In this study, mixed pixel analysis of ASTER image has carried out using IKONOS image and DSM. For mixed pixel analysis, high accurated geometric correction was required. Image matching method was applied for generating GCP datasets. IKONOS image was rectified by affine transform. After that, one pixel in ASTER image should be compared with corresponded 15×15 pixel in IKONOS image. Then, training dataset were generated for mixed pixel analysis using visual interpretation of IKONOS image. Finally, classification will be carried out based on Linear Mixture Model. Shadow extraction might be succeeded by the classification. The extracted shadow area was validated using shadow image which generated from 1m${\sim}$2m spatial resolution DSM. The result showed 17.2% error was occurred in mixed pixel. It might be limitation of ASTER image for shadow extraction because of 8bit quantization data.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.176-178
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• 2005

In the images of a video camera employed for surveillance, detecting targets by extracting foreground image is of great importance. The foreground regions detected, however, include not only moving targets but also their shadows. This paper presents a novel technique to detect shadow pixels in the foreground image of a video camera. The image characteristics of video cameras employed, a web-cam and a CCD, are first analysed in the HSV color space and a pixel-level shadow detection technique is proposed based on the analysis. Compared with existing techniques where unified criteria are used to all pixels, the proposed technique determines shadow pixels utilizing a fact that the effect of shadowing to each pixel is different depending on its brightness in background image. Such an approach can accommodate local features in an image and hold consistent performance even in changing environment. In experiments targeting pedestrians, the proposed technique showed better results compared with an existing technique.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.3
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• pp.202-208
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• 2013

In the image processing for VS (Video Surveillance), the detection of moving entities in a monitored scene is an important step. A background subtraction technique has been widely employed to find the moving entities. However, the extracted foreground regions often include not only real entities but also their cast shadows, and this can cause errors in following image processing steps, such as tracking, recognition, and analysis. In this paper, a novel technique is proposed to determine the shadow pixels of moving objects in the foreground image of a VS camera. Compared to existing techniques where the same decision criteria are applied to all moving pixels, the proposed technique determines shadow pixels using local features based on two facts: First, the amount of pixel intensity drop due to a shadow depends on the intensity level of background. Second, the distribution pattern of pixel intensities remains even if a shadow is cast. The proposed method has been tested at various situations with different backgrounds and moving humans in different colors.

• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.987-989
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• 2006

1.52" $130(RGB){\times}130$ full color PM OLED device with $70\;{\mu}m{\times}210\;{\mu}m$ of sub-pixel pitch was fabricated using shadow mask method for metal cathode deposition. Instead of conventional patterning process to form cathode separator via photolithography, regularly patterned shadow mask was applied to deposit metal cathode in this OLED display. Metal cathode was patterned via 2-step evaporation using shadow mask with shape of rectangular stripe and its alignment margin is $2.5\;{\mu}m$. Technical advantages of this method include reduction of process time according to skipping over photolithographic process for cathode separator and minimizing pixel shrinkage caused by PR cathode separator as well as improving lifetime of OLED device.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.357-359
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• 2003

There is various problem in grasping change of vegetation by NDVI, PVI, etc. It is very difficult especially to remove various noise ingredients in the received satellite data. Until now, it is difficult to compensate for shadow effect when NDVI is used in vegetation analysis. The essence of this study is to describe data simulation and then applied the result to the NOAA AVHRR data. When a pixel contains shadow more than 60% then this pixe1 is extracted for shadow effects on NDVI.

• Journal of Korea Game Society
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• v.14 no.2
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• pp.77-84
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• 2014

Presence of soft shadow effects from an area light makes virtual scenes look more realistic. However, since computation of soft shadow effects takes a long time, acceleration methods are required to apply it to real-time 3D applications. Many researches assumed that area lights are white rectangles. We suggest a new method which renders soft shadows under the area light source having arbitrary shape and color. In order to approximate visibility test, we use a shadow mapping result near a pixel. Complexity of shadow near a pixel is used to determine degree of precision of our visibility estimation. Finally, our method can present more realistic soft shadows for the area light that have more general shape and color in real-time.

• Journal of Korea Game Society
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• v.20 no.3
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• pp.65-74
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• 2020

In the shadow map method, if the shadow map is magnified, the shadow has a jagged silhouette. Herein, we propose a soft shadow method that filters reshaped silhouettes analytically. First, the shadow silhouette is reshaped through sub-texel edge detection, which is based on linear or quadratic curve models. Second, an integral shadow filtering algorithm is used to accurately obtain the average shadow intensity from a definite integral estimation. The implementation demonstrates that our solution can effectively eliminate jagged aliasing and efficiently generate soft shadows.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.395-402
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• 2005

Object extraction is needed to track objects in color traffic image sequence. To extract objects, we use background differencing method based on MOG(Mixture of Gaussians). In extracted objects, shadows may be included. Due to shadows, we may not find exact location of objects and sometimes we find adjacent objects are glued together. Many methods have been proposed to remove shadows. Conventional methods usually assume that color and texture information are preserved under the shadow. Thus these methods do not work well if these assumptions do not hold. In this paper, we propose a new robust shadow removal method which works well in those situations. First we extract shadow pixel candidates by analysing color information and compute the ratio of shadow pixel candidates over the total number of Pixels. W the ratio is reasonable, we remove shadow candidate Pixels and if not, we use data in history array containing Previous removal records. We applied the method to real color traffic image sequences and obtained good results.

• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.400-407
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• 2019

In this paper, the shadow detection and reconstruction method are proposed using intrinsic image, which does not change the essential characteristics under the influence of various illuminance, and multi-scale gamma correction. The shadow detection was estimated by the pixel change information between a grayscale and an intrinsic image of the color image, and the brightness of the image were adjusted by gamma correction in the shadow restoration process. Multi-scale gamma correction is performed for each channel of a color image due to the fact that the saturation can be changed by nonlinear adjustment to individual pixel values. Multi-scale gamma values are estimated based on the information of the crossed edge between shadows and non-shadowed regions in the color image, as a result, the shadows are reconstructed by correcting different region features with multi-scale gamma values. Experimental results show that the proposed method effectively reconstructs shadows in a single natural image.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.877-891
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• 2018

In this paper, we propose a novel algorithm for rendering motion-blurred shadows utilizing a depth-time ranges shadow map. First, we render a scene from a light source to generate a shadow map. For each pixel in the shadow map, we store a list of depth-time ranges. Each range has two points defining a period where a particular geometry was visible to the light source and two distances from the light. Next, we render the scene from the camera to perform shadow tests. With the depths and times of each range, we can easily sample the shadow map at a particular receiver and time. Our algorithm runs entirely on GPUs and solves various problems encountered by previous approaches.