• The Journal of the Korea Contents Association
• /
• v.5 no.4
• /
• pp.103-110
• /
• 2005

In this paper, we present a shadow detection algorithm using the shadow features which appear in color images. Shadow regions have lower luminance and saturation than those of nearby regions, and is generally shown as dark colors. The regions are detected by means of analysing and applying their properties to images represented as the HSI color model. The proposed algorithm is consisted of two steps: at the first step, the candidate regions of shadow are found with using shadow features, and then, real shadow regions are detected only in candidate regions by using their information to reduce real objects and dark marks. The experimental results show that the algorithm is effective.

• Korean Journal of Remote Sensing
• /
• v.16 no.3
• /
• pp.235-242
• /
• 2000

This paper presents a method to detect buildings using shadow information in satellite imagery. We classify image into three categories of building region, shadow region and background region to find buildings with consistent intensity. After the removal of noises in building regions and shadow regions, buildings adjacent to shadow regions are detected using the constraint of building and shadow sizes. The algorithm has been applied to KOMPSAT and SPOT images and the result showed buildings are efficiently detected.

• Proceedings of the Korea Contents Association Conference
• /
• 2009.05a
• /
• pp.889-894
• /
• 2009

Accompanied by the rapid development of Computer Vision, Visual surveillance has achieved great evolution with more and more complicated processing. However there are still many problems to be resolved for robust and reliable visual surveillance, and the cast shadow occurring in motion detection process is one of them. Shadow pixels are often misclassified as object pixels so that they cause errors in localization, segmentation, tracking and classification of objects. This paper proposes a novel cast shadow removal method. As opposed to previous conventional methods, which considers pixel properties like intensity properties, color distortion, HSV color system, and etc., the proposed method utilizes observations about edge patterns in the shadow region in the current frame and the corresponding region in the background scene, and applies Laplacian edge detector to the blob regions in the current frame and the background scene. Then, the product of the outcomes of application determines whether the blob pixels in the foreground mask comes from object blob regions or shadow regions. The proposed method is simple but turns out practically very effective for Gaussian Mixture Model, which is verified through experiments.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2004.02a
• /
• pp.64-72
• /
• 2004

Correction of shadow effects is critical step for image interpretation and feature extraction from aerial imagery. In this paper, an efficient algorithm to correct shadow effects from aerial color imagery is presented. The following steps have been performed to remove the shadow effect. First, the shadow regions are precisely located using the solar position and the height of ground objects derived from LIDAR (Light Detection and Ranging) data. Subsequently, segmentation of context regions is implemented for accurate correction with existing digital map. Next step, to calculate correction factor the comparison between the context region and the same non-shadowed context region is made. Finally, corrected image is generated by correcting the shadow effect. The result presented here helps to accurately extract and interpret geo-spatial information from aerial color imagery

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2003.10a
• /
• pp.397-402
• /
• 2003

This study is aimed to improve the quality of image fusion results through shadow effects correction. For this, shadow effects correction algorithm is proposed and visual comparisons have been made to estimate the quality of image fusion results. The following four steps have been performed to improve the image fusion qualify First, the shadow regions of satellite image are precisely located. Subsequently, segmentation of context regions is manually implemented for accurate correction. Next step, to calculate correction factor we compared the context region with the same non-shadow context region. Finally, image fusion is implemented using collected images. The result presented here helps to accurately extract and interpret geo-spatial information from satellite imagery.

• Journal of Korea Multimedia Society
• /
• v.17 no.4
• /
• pp.420-432
• /
• 2014

In detection of moving objects from video sequences, an essential process for intelligent visual surveillance, the cast shadows accompanying moving objects are different from background so that they may be easily extracted as foreground object blobs, which causes errors in localization, segmentation, tracking and classification of objects. Most of the previous research results about moving cast shadow detection and removal usually utilize color information about objects and scenes. In this paper, we proposes a novel cast shadow removal method of moving objects in gray level video data for visual surveillance application. The proposed method utilizes observations about edge patterns in the shadow region in the current frame and the corresponding region in the background scene, and applies Laplacian edge detector to the blob regions in the current frame and the corresponding regions in the background scene. Then, the product of the outcomes of application determines moving object blob pixels from the blob pixels in the foreground mask. The minimal rectangle regions containing all blob pixles classified as moving object pixels are extracted. The proposed method is simple but turns out practically very effective for Adative Gaussian Mixture Model-based object detection of intelligent visual surveillance applications, which is verified through experiments.

• Journal of the Korean Geotechnical Society
• /
• v.39 no.12
• /
• pp.75-91
• /
• 2023

In this study, we explore the use of ground penetrating radar (GPR) for the nondestructive survey of subsurface conduits, focusing on the challenges posed by multichannel environments. A key concern is the shadow regions created by conduits, which significantly impact survey results. The shadow regions, which are influenced by conduit position and diameter, hinder signal propagation, thereby making detection within these regions challenging. Using finite-difference time-domain numerical analysis, we examined the characteristics of conduit signals, which typically manifest in hyperbolic patterns. Particularly, we investigated three conduit arrangements: horizontal, vertical, and diagonal. Automatic gain control was applied to amplify the signals, enabling the analysis of variations in shadow regions and signal characteristics for each arrangement. In the horizontal arrangement, the proximity of the two conduits resulted in the emergence of a new hyperbolic pattern between the existing conduits. In the vertical arrangement, the lower conduit could be detected using hyperbolic signals on either side, but the detection was challenging when the upper conduit diameter exceeded that of the lower conduit. In the diagonal arrangement, signal characteristics varied based on the position of shadow regions relative to the detection range of the equipment. Asymmetrical signal patterns were observed when the shadow regions fell within the detection range, whereas the signals of the two conduits were minimally impacted when the shadow regions were outside the detection range. This study provides vital insights into accurately detecting and characterizing subsurface multichannel conduits using GPR-a significant contribution to the field of subsurface exploration and management.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.3
• /
• pp.11-19
• /
• 2008

Background subtraction, which separates moving objects in video sequences, is an essential technology for object recognition and tracking. However, background subtraction methods are often confused by shadow regions and this misclassification of shadow regions disturbs further processes to perceive the shapes or exact positions of moving objects. This paper proposes a method for shadow elimination which is based on shadow modeling by color information and Bayesian classification framework. Also, because of dynamic update of modeling parametres, the proposed method is able to correspond adaptively to illumination changes. Experimental results proved that the proposed method can eliminate shadow regions effectively even for circumstances with varying lighting condition.

• Journal of Astronomy and Space Sciences
• /
• v.40 no.4
• /
• pp.149-171
• /
• 2023

ShadowCam is a National Aeronautics and Space Administration Advanced Exploration Systems funded instrument hosted onboard the Korea Aerospace Research Institute (KARI) Korea Pathfinder Lunar Orbiter (KPLO) satellite. By collecting high-resolution images of permanently shadowed regions (PSRs), ShadowCam will provide critical information about the distribution and accessibility of water ice and other volatiles at spatial scales (1.7 m/pixel) required to mitigate risks and maximize the results of future exploration activities. The PSRs never see direct sunlight and are illuminated only by light reflected from nearby topographic highs. Since secondary illumination is very dim, ShadowCam was designed to be over 200 times more sensitive than previous imagers like the Lunar Reconnaissance Orbiter Camera Narrow Angle Camera (LROC NAC). ShadowCam images thus allow for unprecedented views into the shadows, but saturate while imaging sunlit terrain.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.6
• /
• pp.2289-2301
• /
• 2015

Mobile devices are becoming powerful enough to realize augmented reality (AR) application. This paper introduces two AR methods to estimate an environmental illumination distribution of a scene. In the first method, we extract the lighting direction and intensity from input images captured with a front-side camera of a mobile device, using its orientation sensor. The second method extracts shadow regions cast by three dimensional (3D) AR marker of known shape and size. Because previous methods examine per pixel shadow intensity, their performances are much affected by the number of sampling points, positions, and threshold values. By using a simple binary operation between the previously clustered shadow regions and the threshold real shadow regions, we can compute efficiently their relative area proportions according to threshold values. This area-based method can overcome point sampling problem and threshold value selection. Experiment results demonstrate that the proposed methods generate natural image with multiple smooth shadows in real-time.