• The KIPS Transactions:PartB
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• v.15B no.1
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• pp.1-8
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• 2008

Generally, moving objects in surveillance video are extracted by background subtraction or frame difference method. However, moving cast shadows on object distort extracted figures which cause serious detection problems. Especially, analyzing vehicle information in video frames from a fixed surveillance camera on road, we obtain inaccurate results by shadow which vehicle causes. So, Shadow Elimination is essential to extract right objects from frames in surveillance video. And we use shadow removal algorithm for vehicle classification. In our paper, as we suppress moving cast shadow in object, we efficiently discriminate vehicle types. After we fit new object of shadow-removed object as three dimension object, we use extracted attributes for supervised learning to classify vehicle types. In experiment, we use 3 learning methods {IBL, C4.5, NN(Neural Network)} so that we evaluate the result of vehicle classification by shadow elimination.

• Korean Journal of Remote Sensing
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• v.22 no.2
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• pp.123-129
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• 2006

High-resolution aerial color image offers great possibilities for geometric and semantic information for spatial data generation. However, shadow casts by buildings and trees in high-density urban areas obscure much of the information in the image giving rise to potentially inaccurate classification and inexact feature extraction. Though many researches have been implemented for solving shadow casts, few studies have been carried out about the extraction of features hindered by shadows from aerial color images in urban areas. This paper presents a asphalt road boundary extraction technique that combines information from aerial color image and LIDAR (LIght Detection And Ranging) data. The following steps have been performed to remove shadow effects and to extract road boundary from the image. First, the shadow regions of the aerial color image are precisely located using LEAR DSM (Digital Surface Model) and solar positions. Second, shadow regions assumed as road are corrected by shadow path reconstruction algorithms. After that, asphalt road boundary extraction is implemented by segmentation and edge detection. Finally, asphalt road boundary lines are extracted as vector data by vectorization technique. The experimental results showed that this approach was effective and great potential advantages.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.4
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• pp.231-234
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• 2013

This paper introduces a mixture of background subtraction technique and K-Means clustering algorithm for removing shadows from video sequences. Lighting conditions cause an issue with segmentation. The proposed method can successfully eradicate artifacts associated with lighting changes such as highlight and reflection, and cast shadows of moving object from segmentation. In this paper, K-Means clustering algorithm is applied to the foreground, which is initially fragmented by background subtraction technique. The estimated shadow region is then superimposed on the background to eliminate the effects that cause redundancy in object detection. Simulation results depict that the proposed approach is capable of removing shadows and reflections from moving objects with an accuracy of more than 95% in every cases considered.

• 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 the Korean Society for Precision Engineering
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• v.22 no.9 s.174
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• pp.20-26
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• 2005

• Journal of the Korea Computer Graphics Society
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• v.24 no.3
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• pp.43-48
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• 2018

In this paper, we present a method for removing shadows from scanned documents. Compared to the existing methods such as one based on image pyramid representation or adaptive thresholding, our method produces more robust and higher quality results. The basic idea of the approach is to use the local image statistics and to separate interesting regions from the image such as the regions around letters and figures. For the separated regions, we adaptively adjust the local brightness and contrast, and apply the sigmoid function to the intensity values as well to enhance the clarity of the image. For separated the other empty regions, we apply the gradient-base image hole filling method to fill the region with smooth color change.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.63-72
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• 2020

Shadow banking in China has been growing rapidly; banks use wealth management products aggressively to evade regulatory constraints. The loan-to-deposit ratio or LDR targets both sides of the balance sheet; loans in terms of asset-side, and deposits in terms of liabilities-side; banks needed to control and maintain both sides. Regulators restricted Chinese banks to maintain a 75% limit for their loan-depositratio. Banks' needed to either lower their loans or increase the deposits; WMPs helped banks to evade this limit. Banks issue more WMPs to control and manage a 75% statutory ceiling LDR. This WMPs-LDR positive association disappeared post-2015 period. This study empirically examined how Chinese banks use WMPs issuance to avoid regulatory constraints. Quarterly panel data for 30 top Chinese banks were used by analyzing pre-2015 (during the 75% LDR limit) and post-2015 (after removal of the LDR limit). This study also performed fixed-effects model as recommended by the Hausman specification test, with feasible generalized least squares FGLS estimation technique. The results of this study show that for the pre-2015 period, Chinese banks use issuance of WMPs aggressively to manage their LDR limit; this WMPs-LDR relationship disappeared post-2015 period. Moreover, SMBs use WMPs more eagerly as compare to Big4 banks.

• Journal of information and communication convergence engineering
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• v.16 no.2
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• pp.114-124
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• 2018

This paper illustrates a vision-based vehicle positioning method at an intersection to support the C-ITS. It removes the minor shadow that causes the merging problem by simply eliminating the fractional parts of a quotient image. In order to separate the occlusion, it firstly performs the distance transform to analyze the contents of the single foreground object to find seeds, each of which represents one vehicle. Then, it applies the watershed to find the natural border of two cars. In addition, a general vehicle model and the corresponding space estimation method are proposed. For performance evaluation, the corresponding ground truth data are read and compared with the vision-based detected data. In addition, two criteria, IOU and DEER, are defined to measure the accuracy of the extracted data. The evaluation result shows that the average value of IOU is 0.65 with the hit ratio of 97%. It also shows that the average value of DEER is 0.0467, which means the positioning error is 32.7 centimeters.

• Journal of the Korean Society for Marine Environment & Energy
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• v.19 no.4
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• pp.341-348
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• 2016

Micro-algae, one of the biological resources for alternative energy, has been heavily studied. Among various methods to analyze the status of the micro-algae including counting, screening, and flocculation, the flocculation approach has been widely accepted in many critical applications such as red tide removal study or microalgae resource study. To characterize the flocculation status of the micro-alga. A traditional optical modality, i.e., photospectrometry, measuring the optical density of the flocs has been frequently employed. While this traditional optical method needs shorter time than the counting method in flocculation status analysis, it has relatively lower detection accuracy. To address this issue, a novel real-time micro-algae flocculation analysis method based on the lens-free shadow imaging technique (LSIT) is introduced. Both single cell detection and floc detection are simultaneously available with a proposed lens-free shadow image, confirmed by comparing the results with optical microscope images. And three shadow parameters, e.g., number of flocs, effective area of flocs, and maximum size of floc, enabling quantification of the flocculation phenomenon of micro-alga, are firstly demonstrated in this article. The efficacy of each shadow parameter is verified with the real-time flocculation monitoring experiments using custom developed cohesive agents.

• Journal of Chest Surgery
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• v.26 no.7
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• pp.548-551
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• 1993

Calcified right ventricular thrombi are very rare.One case of large clacified thrombus in right ventricle being seen in a 65-year old man, is presented. He had dyspnea and generalized edema.The chest film showed a large calcified mass in cardiac shadow especially in lateral view.On echocardiography and chest computed tomography, large calcified mass density occupied nearly entire right ventricular outflow tract.The mass removal was performed through right ventriculotomny.The mass was whitish, stony hard, measured 4 cm x 4.5 cm x 8 cm, tightly attached to right ventricular infundibular septum and ventriculoinfundibular fold.