• Journal of Digital Contents Society
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• v.15 no.4
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• pp.521-526
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• 2014

The purpose of this study is to propose the efficient method of 3D data registration. Three-dimensional data including the two-dimensional image acquisition apparatus and the position information are acquired at an arbitrary angle with each other. This paper proposes the more accurate and faster matching method by using this information. Four image points founded from 2D images match the volumetric size of the model and compute the homography of the axis for registration between two 3D data sets. The advantages of the proposed algorithm are the repeating process is unnecessary and the process time is faster than prvious method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5385-5391
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• 2013

As on-line purchases is activated, customers' demand increases for the realistic and accurate digital information of a product design. In this paper, we propose a practical method that can generate a realistic 3D model of a real product using a 3D geometry obtained by a 3D scanner and its photographic images. In order to register images to the 3D geometry, the camera focal length, the CCD scanning aspect ratio and the transformation matrix between the camera coordinate and the 3D object coordinate must be determined. To perform this 2D-3D registration with consideration of computational complexity, a three-step method is applied, which consists of camera calibration, determination of a temporary optimum translation vector (TOTV) and nonlinear optimization for three rotational angles. A case study for a metallic coated industrial part, of which the colour appearance is hardly obtained by a 3D colour scanner has performed to demonstrate the effectiveness of the proposed method.

• Imaging Science in Dentistry
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• v.53 no.1
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• pp.21-26
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• 2023

Purpose: A fully digital approach to oral prosthodontic rehabilitation requires the possibility of combining (i.e., registering) digital documentation from different sources. This becomes more complex in an edentulous jaw, as fixed dental markers to perform reliable registration are lacking. This validation study aimed to evaluate the reproducibility of 1) intraoral scanning and 2) soft tissue-based registration of an intraoral scan with a cone-beam computed tomography (CBCT) scan for a fully edentulous upper jaw. Materials and Methods: Two observers independently performed intraoral scans of the upper jaw in 14 fully edentulous patients. The palatal vault of both surface models was aligned, and the inter-observer variability was assessed by calculating the mean inter-surface distance at the level of the alveolar crest. Additionally, a CBCT scan of all patients was obtained and a soft tissue surface model was generated using patient-specific gray values. This CBCT soft tissue model was registered with the intraoral scans of both observers, and the intraclass correlation coefficient(ICC) was calculated to evaluate the reproducibility of the registration method. Results: The mean inter-observer deviation when performing an intraoral scan of the fully edentulous upper jaw was 0.10±0.09 mm. The inter-observer agreement for the soft tissue-based registration method was excellent(ICC=0.94; 95% confidence interval, 0.81-0.98). Conclusion: Even when teeth are lacking, intraoral scanning of the jaw and soft tissue-based registration of an intraoral scan with a CBCT scan can be performed with a high degree of precision.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.456-463
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• 2003

This paper presents a texture mapping method of a 3D scanned model with 2D images from different views. The texture mapping process consists of two steps Registration of the 3D facet model to the images by interactive points matching, and 3D texture mapping of the image pieces to the corresponding facets. In this paper. some implem entation issues and illustrative examples are described.

• Journal of KIISE:Software and Applications
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• v.30 no.12
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• pp.1239-1246
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• 2003

Registration is the process aligning the range data sets from different views in a common coordinate system. In order to achieve a complete 3D model, we need to refine the data sets after coarse registration. One of the most popular refinery techniques is the iterative closest point (ICP) algorithm, which starts with pre-estimated overlapping regions. This paper presents an improved ICP algorithm that can automatically register multiple 3D data sets from unknown viewpoints. The sensor projection that represents the mapping of the 3D data into its associated range image is used to determine the overlapping region of two range data sets. By combining ICP algorithm with the sensor projection constraint, we can make an automatic registration of multiple 3D sets without pre-procedures that are prone to errors and any mechanical positioning device or manual assistance. The experimental results showed better performance of the proposed method on a couple of 3D data sets than previous methods.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.6
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• pp.303-310
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• 2023

A single vision system limits the ability to accurately understand the spatial constraints and interactions between robots and dynamic workers caused by gantry robots and collaborative robots during production manufacturing. In this paper, we propose a 3D pose registration method for dynamic workers based on a multi-domain vision system for safety monitoring in manufacturing environments. This method uses OpenPose, a deep learning-based posture estimation model, to estimate the worker's dynamic two-dimensional posture in real-time and reconstruct it into three-dimensional coordinates. The 3D coordinates of the reconstructed multi-domain vision system were aligned using the ICP algorithm and then registered to a single 3D coordinate system. The proposed method showed effective performance in a manufacturing process environment with an average registration error of 0.0664 m and an average frame rate of 14.597 per second.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.175-176
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• 2006

The aim of the 3D medical imaging is to facilitate the creation of clinically usable image-based algorithm. Clinically usable imaging algorithm for image analysis requires a high degree of interaction to verify and correct results from registration algorithms, such as the Insight Toolkit (ITK) and the Visualization Toolkit (VTK) which are the class libraries. ITK provides segmentation algorithms and VTK has powerful 3D visualization. However, to apply those libraries to the medical images such as Computerized Tomography (CT), the algorithm based on the interactive construction and modification of data objects are necessary. In this paper we showed the 3D registration about mandibular premolar of human teeth acquired by micro-CT scanner. Also, we used the ITK to find the contour of pulp layer of premolar, furthermore, the 3D imaging was visualized with VTK designed to create one kind of view on the data of 3D visualization. Finally, we evaluated that the volume model of pulp layer would be useful for the tooth morphology in dental medicine.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.6
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• pp.114-122
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• 2011

We propose an automatic localization technique based on Uniform Arc Length Sampling (UALS) of 360 degree range sensor data. The proposed method samples 3D points from dense a point-cloud which is acquired by the sensor, registers the sampled points to a digital surface model(DSM) in real-time, and determines the location of an Unmanned Ground Vehicle(UGV). To reduce the sampling and registration time of a sequence of dense range data, 3D range points are sampled uniformly in terms of ground sample distance. Using the proposed method, we can reduce the number of 3D points while maintaining their uniformity over range data. We compare the registration speed and accuracy of the proposed method with a conventional sample method. Through several experiments by changing the number of sampling points, we analyze the speed and accuracy of the proposed method.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.2
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• pp.192-205
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• 2011

This study analyzed the registration of patent and utility models by fashion firms in Korea. A total of 2,291 registration cases of IPC A41B-H from the period of 1996 to 2009 were collected by KIPRIS of the Korean Intellectual Property Organization (KIPO). All cases were analyzed by year to review the longitudinal trend and 481 cases of IPC A41B (shirts, underwear, baby linen, and handkerchiefs) and 1088 cases of IPC A41D (outerwear, protective garments, and accessories) were analyzed by content (provided benefit type and developing method), by detailed product items and the characteristics of the applicant. The results of this study were as follows: 1) Registration of IPC 41 increased steeply by the year (especially since 2006) and the patent registrations increased more than those in the utility model. 2) Analyzing the application content of A41B on the basis of benefit showed that 75% were to provide new functions and the rest were for health. In terms of the developing method, 83% of benefit provided by the application were by design development, 11.2% were by material, and the rest was by process, In the cases of IPC A41D, 23.6% were for safety and protection. In terms of the developing method, the process and material development were more frequently adopted than in the cases of A41B. 3) The major product types of A41B were socks, underwear, and infant wear, whereas gloves and parts of clothing were major items in A41D. 4) In terms of the characteristics of the applicant, registration by firms was greater for patents than for utility models and registration by foreigners increased in 2006 due to the complete opening of the retail market. 5) Fifteen universities registered for a total 57 cases and major applications were for IT related clothing or high-tech protective items.

• Korean Journal of Computational Design and Engineering
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• v.21 no.3
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• pp.296-305
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• 2016

This paper proposes a framework to automatically align Dental range image captured by depth sensors like the Microsoft Kinect. Aligning dental images by intraoral scanning technology is a difficult problem for applications requiring accurate model of dental-scan datasets with efficiency in computation time. The most important thing in dental scanning system is accuracy of the dental prosthesis. Previous approaches in intraoral scanning uses a Z-buffer ICP algorithm for fast registration, but it is relatively not accurate and it may cause cumulative errors. This paper proposes additional Alignment using the rough result comes after intraoral scanning alignment. It requires that Each Depth Image of the total set shares some overlap with at least one other Depth image. This research implements the automatically additional alignment system that aligns all depth images into Completed model by computing a network of pairwise registrations. The order of the each individual transformation is derived from a global network and AABB box overlap detection methods.