• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.237-242
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• 2003

During the past, digital orthophoto is generated for rural area or low resolution image, because the accurate extraction of DEM is difficult for urban area. But, nowadays, high resolution DEM by ALS system starts to become available for urban area, so the importance of large scale digital orthophoto generation becomes increasing. In this paper, we propose and describe effective algorithm for detecting occlusion area and not only restoring occlusion area but also processing null pixels by occlusion area for minimizing the heterogeneity of digital orthophoto. With proposed algorithm, we detected occlusion area due to height of structures such as buildings, bridges, etc, and restored occlusion area using reference image. Also, The homogeneity of generated digital orthophoto was improved by using brightness correction.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.417-422
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• 2008

With standard orthorectification algorithms, one can produce unacceptable structure duplication in the orthophoto due to the double projection. Because of the abrupt height differences, such structure duplication is a frequently occurred phenomenon in the dense urban area which includes multi-history buildings. Therefore, occlusion area detection especially for the urban area is a critical issue in generation of true orthophoto. This paper deals with occlusion area detection with visible height based approach from aerial imagery and LiDAR. In order to accomplish this, a grid format DSM is produced from the point clouds of LiDAR. Next, visible height based algorithm is proposed to detect the occlusion area for each camera exposure station with DSM. Finally, generation of true orthophoto is presented with DSM and previously produced occlusion maps. The proposed algorithms are applied in the Purdue campus, Indiana, USA.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.4
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• pp.267-273
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• 2005

Stereo image analysis has been an important tool for reconstructing 3D terrain. By In its nature, occlusion is one of difficulties Ive cannot avoid in stereo matching. This paper presents a study on occlusion detection by employing LRC(Left-Right Check) and OCC(Occlusion Constraint) and how we can improve the accuracy of DEM(Digital Elevation Model) y using interpolated data into the detected occluded area. Experimental results show that these method can effectively detect occluded regions and improve the accuarcy of DEM using the occlusion detection.

• Journal of Biomedical Engineering Research
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• v.22 no.6
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• pp.551-557
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• 2001

Occlusion of the dural-sac in the lumbar spine was quantitatively analysed using a one motion segment finite element mode developed in this study. Occlusion was quantified by calculating the cross sectional area chance of the dural-sac. In static analysis. less than 2 kN of compressive load could Produced no dural-sac occlusion. whereas 6kN load reduced cross sectional area by 4%, and produced 7.4%, 10.5% occlusion for additional 8 Nm. 10 Nm extension moments. respectively. In creep analysis, 10 Nm extension reduced cross sectional area and volume of the dural-sac by 6.9% and 2.4%, respectively. However. flexion moment could not produce any occlusion. The results suggested that occlusions may result mainly from slackening of ligamentum flavum and disc budging.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.144-146
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• 2004

Stereo image analysis has been an important tool for reconstructing 3D terrain. By In its nature, occlusion is one of difficulties we cannot avoid in stereo matching. This paper presents a study on occlusion detection by employing LRC(Left-Right Check) and OCC(Occlusion Constraint). Experimental results show that these method can effectively detect occluded regions and those regions are usually occurred around object contours and scene discontinuity.

• Journal of Drive and Control
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• v.19 no.3
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• pp.9-15
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• 2022

This paper proposes a method for constructing and verifying datasets used in deep learning technology, to prevent safety accidents in automated construction machinery or autonomous vehicles. Although open datasets for developing image recognition technologies are challenging to meet requirements desired by users, this study proposes the interface of virtual simulators to facilitate the creation of training datasets desired by users. The pixel-level training image dataset was verified by creating scenarios, including various road types and objects in a virtual environment. Detecting an object from an image may interfere with the accurate path determination due to occlusion areas covered by another object. Thus, we construct a database, for developing an occlusion area detection algorithm in a virtual environment. Additionally, we present the possibility of its use as a deep learning dataset to calculate a grid map, that enables path search considering occlusion areas. Custom datasets are built using the RDBMS system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.83-92
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• 2010

Emergence of high-resolution digital aerial cameras and airborne laser scanners have made innovative progress in photogrammetry and spatial information technology. The purpose of this study is to generate true orthoimage by recovering occlusion areas. The orthoimages were generated patch-based transformation. The occlusion areas were mutually corrected by using multiple aerial images. This study proposed a novel method of building roof based orthoimage generation and an effective method of occlusion area detection and recovery. The proposed methods could be efficient to generate true orthoimages in urban areas where occlusion areas are problematic.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.186-191
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• 2019

Introduction: In aged people, stroke incidence is increased. But standardized experimental animal protocol study for the research of stroke therapy is rare. There is little report on the success rate of cerebral artery occlusion model using standardized Nylon thread length of precise thread end-size controlled. Method: In this study, the operator intended the occlusion of middle cerebral artery (MCA) using $0.18{\pm}0.02mm$ end 5-0 Nylon thread. Middle cerebral artery occlusion was induced for 60min under isoflurane anesthesia. After 60min, the operator removed the Nylon thread and reperfusion was induced for 23hrs. The mice was killed 23hrs after reperfusion and infarction area of brain was confirmed by 1.5% TTC (2,3,5-tryphenyl tetrazolium chloride) staining. Results: According to end size and insert length of Nylon thread, Middle cerebral artery occlusion (n=50), internal carotid artery occlusion (n= 14), distal middle cerebral artery occlusion (n= 36), anterior cerebral artery (n= 1) were induced. And no infarction (n= 50) was observed. Conclusion: According to weight of mice, the operator induced reversible cerebral artery occlusion model by different insert length (30.0~36.9g : 9.0mm, 37.0~40.0g : 9.5mm) of Nylon thread. Success of cerebral artery occlusion model was confirmed by checking infarction area using TTC staining. The success rate (66.9%, 101/151) of reversible cerebral artery occlusion model in the mouse and the operational conditions are shown.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.5
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• pp.317-324
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• 2015

In his paper, we propose the graphic-based direction tracking system that be able to detect the current location and direction of the flight object and virtually run the pointing to the flight direction when a small UAV is located in the occlusion area behind buildings or obstacles in the moving surveillance systems. Based on the experimental results about the simulation flight path extracted from the Mission Planner we found the proposed system operates the desired flight mission effectively in tracking.

• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.663-670
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• 2006

For virtual target to be displaying on real image realistically, it is essential to determine the location of the virtual object together with producing the occlusions area after registering two world. In this paper, we propose the new method to solve occlusions which happens during virtual target moves according to the simulated route on real image. For this purpose, we first construct three dimensional virtual world by DEM of experimental area and register CCD camera image on it by visual clues. Next, we also propose a method to solve the occlusion using snake and picking algorithm which can extract the three dimensional information of the position happening occlusion in the image and can use it when target moves that area. In the experiment, we proved the effectiveness of the proposed method in the environment which a partial occlusions happens.