• Journal of Institute of Convergence Technology
• /
• v.7 no.2
• /
• pp.17-20
• /
• 2017

Orthodontic treatment is accomplished by attaching an archwire to a bracket on tooth. The shape of the archwire is usually planned from 3-D scanned data of patient's teeth. It is manufactured by bending a metal wire and there have been some researches in progress to automate it. In this paper, we propose a method to obtain the bending angle at the bending point from the shape data of the archwire and verify it by simulation using actual archwire data.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2001.04a
• /
• pp.435-438
• /
• 2001

Reverse engineering technology refers to the process that creates a CAD model of an existing part using measuring devices. Recently, non-contact scanning devices have become more accurate and the speed of data acquisition has increased drastically. However, they generate thousands of points per second and various types of point data. Therefore, it becomes a major issue to handle the huge amount and various types of point data. To generate a CAD model from scanned point data efficiently, these point data should be well arranged through point data handling processes such as data reduction and segmentation. This paper proposes a new point data handling method using 3D grids. The geometric information of a part is extracted from point cloud data by estimating normal values of the points. The non-uniform 3D grids for data reduction and segmentation are generated based on the geometric information. Through these data reduction and segmentation processes, it is possible to create CAD models autmatically and efficiently. The proposed method is applied to two quardric medels and the results are discussed.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2003.06a
• /
• pp.1283-1287
• /
• 2003

Reverse engineering technology refers to the process that creates a CAD model of an existing part using measuring devices. Recently, non-contact scanning devices have become more accurate and the speed of data acquisition has increased drastically. However, they generate thousands of points per second and various types of point data. Therefore. it becomes a important to handle the huge amount and various types of point data to generate a surface model efficiently. This paper proposes a new triangular mesh generation method using 3D grids. The geometric information of a part can be obtained from point cloud data by estimating normal values of the points. In our research, the non-uniform 3D grids are generated first for feature based data reduction based on the geometric information. Then, triangulation is performed with the reduced point data. The grid structure is efficiently used not only for neighbor point search that can speed up the mesh generation process but also for getting surface connectivity information to result in same topology surface with the point data. Through this integrated approach, it is possible to create surface models from scanned point data efficiently.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.3
• /
• pp.41-47
• /
• 2019

In this paper, we propose a application of conditional generative adversarial network (cGAN) for generation of contrast enhanced computed tomography (CT) image. Two types of CT data which were the enhanced and non-enhanced were used and applied by the histogram equalization for adjusting image intensities. In order to validate the generation of contrast enhanced CT data, the structural similarity index measurement (SSIM) was performed. Prepared generated contrast CT data were analyzed the statistical analysis using paired sample t-test. In order to apply the optimized algorithm for the lymph node cancer, they were calculated by short to long axis ratio (S/L) method. In the case of the model trained with CT data and their histogram equalized SSIM were $0.905{\pm}0.048$ and $0.908{\pm}0.047$. The tumor S/L of generated contrast enhanced CT data were validated similar to the ground truth when they were compared to scanned contrast enhanced CT data. It is expected that advantages of Generated contrast enhanced CT data based on deep learning are a cost-effective and less radiation exposure as well as further anatomical information with non-enhanced CT data.

• The Research Journal of the Costume Culture
• /
• v.10 no.6
• /
• pp.709-717
• /
• 2002

In the apparel industry, the technology has been advanced rapidly. The use of 3D scanning systems fur the capture and measurement of human body is becoming common place. Three dimensional digital image can be used for design, inspection, reproduction of physical objects. The purpose of this study is to develop a method that drafts men's basic bodice pattern from scanned 3D body surface shape data. In order to pursue this purpose the researchers developed pattern drafting algorithm. The 3D scanner used in this study was Cyberware Whole Body Scanner WB-4. The bodice pattern drafting algorithm from 3D body surface shape data developed in this study is as follows. First, convert geometric 3D body surface data to 3D polygonal mesh data. Second, develop algorithm to lay out 3D polygonal patches onto a plane using Auto Lisp program. The polygon meshes are coplanar, and the individual mesh is continuously in contact with next one The bodice front surface shape data in polygonal patches form was lined up in bust and waist levels. The back bodice was drafted by lining up the polygonal mesh in scapula, chest, and waist levels. in the drafts, gaps between polygons were formed into the darts.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.26 no.10
• /
• pp.1961-1970
• /
• 2002

A laser scanner is widely used fur a device fur acquiring point data in reverse engineering. It is more efficient to generate a surface automatically from the line-typed data than scattered data of points clouds. In the case of a compound model, it is hard to represent all the scanned data into one surface maintaining its original line characteristics. In this paper, a method is presented to generate a surface by the segmentation of measured point data. After forming triangular net, the segmentation is done by the user input such as the angle between triangles, the number of facets to be considered as small segment, and the angle for combining small segment. B-spline fitting is implemented to the point data in each segment. The surface generation through segmentation shows a reliable result when it is applied to the models with curvature deviation regions. An useful algorithm for surface reconstruction is developed and verified by applying an practical model and shows a good tools fur reverse engineering in design modification.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.212-215
• /
• 2022

In the era of so-called digital transformation today, the need for the construction and utilization of big data in various fields has increased. Today, a lot of data is produced and stored in a digital device and media-friendly manner, but the production and storage of data for a long time in the past has been dominated by print books. Therefore, the need for Optical Character Recognition (OCR) technology to utilize the vast amount of print books accumulated for a long time as big data was also required in line with the need for big data. In this study, a system for digitizing the structure and content of a document object inside a scanned book image is proposed. The proposal system largely consists of the following three steps. 1) Recognition of area information by document objects (table, equation, picture, text body) in scanned book image. 2) OCR processing for each area of the text body-table-formula module according to recognized document object areas. 3) The processed document informations gather up and returned to the JSON format. The model proposed in this study uses an open-source project that additional learning and improvement. Intelligent OCR proposed as a system in this study showed commercial OCR software-level performance in processing four types of document objects(table, equation, image, text body).

• Journal of Korea Multimedia Society
• /
• v.19 no.2
• /
• pp.479-486
• /
• 2016

In this paper, the algorithm which can convert a 2D image into a 3D Model will be discussed. The 2D picture drawn by a user is scanned for image processing. The Canny algorithm is employed to find the contour. The waterfront algorithm is proposed to find foreground image area. The foreground area is segmented to decompose the complex shapes into simple shapes. Then, simple segmented foreground image is converted into 3D model to become a complex 3D model. The 3D conversion formular used in this paper is also discussed. The generated 3D model data will be useful for 3D animation and other 3D contents creation.

• International Journal of Human Ecology
• /
• v.14 no.1
• /
• pp.41-55
• /
• 2013

The purpose of this study was to analyze human upper body surface changes at the shoulder and back area. The body surface data were analyzed in terms of muscle and bone displacement in dynamic postures. Body surface data were collected with a 3D body scanner. The body surface was scanned at the static and four baseball batting postures. The body surface dimensions over the deltoids, scapulae and trapezius were measured. The results show that the vertical measurements of the deltoids increased by 20%. The horizontal measurements of the axilla of the back increased. The surface of the trapezius was elongated by over 10%, and the lower back musculature was elongated by about 50%. The results of this study showed that changes in back body surface caused by upper arm movements. It was influenced by the deltoid articulated with the humeri and the scapulae and trapezius. These body surface changes caused by muscle activities and ranges of motion can be used to design functional clothing.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.13 no.4
• /
• pp.49-56
• /
• 2017

It is the approach of embedded system design that finds 3D scanning technology to analyze a real object or environment to collect data on its shape and appearance. 3D laser scanning developed during the last half of 20th century in an attempt to accurately recreate the surfaces of various objects. 1960s, early scanners used lights, cameras, and projectors to carry out the scanning in the lacks of performance which encountered many difficulties with shiny, mirroring, or transparent objects. The 3D scanning technology has leveled-up with helpful of embedded software platform research and design. In this paper, First we designed the hardware of laser/camera setup and turntable moving part which is the base of object. Second, we introduced the process of scanning 3D data with software and analyzed the resulting scanned image on the web server. Last, we made the 3D scanning embedded device with 3D printing model and experimented the 3D scanning performance with Raspberry Pi.