• Journal of Korea Multimedia Society
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• v.12 no.4
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• pp.473-482
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• 2009

Reconstructed 3D data from computer vision includes necessarily a noise or an error. When these data goes through a mesh process, the different 3D mesh data from original shape comes to make by a noise or an error. This paper proposed the method that smooths a noise effectively by noise analysis in reconstructed 3D data. Because the proposed method is smooths a noise using the area ratio of the mesh, the pre-processing of unusable mesh is necessary in 3D mesh data. This study detects a peak noise and Gaussian noise using the ratio of 3D volume and 2D area of mesh and smooths the noise with respect of its characteristics. The experimental results using synthetic and real data demonstrated the efficacy and performance of proposed algorithm.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.2
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• pp.344-353
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• 2004

The purpose of this study was to offer the basis contributes to extract the standardized body data from 3D body measuring for women aged 60 and older. The WB4 of Cyberware was used, and the measuring program of 3D scanning data was 3DM. This study was focused to verify the reliability of 3D data and to offer the effective utilization of 3D measuring on the research for elderly women■s body. Subjects were 19 women aged 60 and older. And three women in late twenties and three dressforms for women were comparing subjects to analyze the signiscant difference by age or human body variable making error. First, 3D scanning was executed twice on each subject, but any significant difference was not appear between two scanning data. So we certifed we could get the consistent and reliable data from the 3D scanner used in this study. Second, the reliability of 3D measuring data was analyzed, and the error range which meant the difference between 3D data and traditional measuring data was analyzed. In elderly women, the significant difference between two data was appeared in 19 body parts. The 7 of 19 were concerned with armpit point. In young women, three significant difference were appeared, and in dressforms, any significant difference was not certified. From these results, we could certify that age or human body variable produced the difference between two data. Third, the data of elderly women from three measuring methods, 3D measuring, traditional measuring, and measuring on 2D photographs were compared. From the result, we found that the 3D measuring data was quite reliable for most body parts excluding some width parts. But in elderly women, there were some limitation to extract reliable data because of their unique body characteristics. In order to be a role of the effective measuring method, the 3D measuring protocol reflected the body characteristics of each age or gender had to be prepared.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1157-1160
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• 1998

This paper describes the design of a block data flow architecture(BDFA) which implements 2-D discrete wavelet transform(DWT)/inverse discrete wavelet transform(IDWT) for real time image processing applications. The BDFA uses 2-D product separable filters for DWT/IDWT. It consists of an input module, a processor array, and an output module. It use both data partitioning and algorithm partitioning to achieve high efficiency and high throughput. The 2-D DWT/IDWT algorithm for 256$\times$256 lenna image has been simulated using IDL(Interactive Data Language). The 2-D array structured BDFA for the 2-D filter has been modeled and simulated using VHDL.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.5
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• pp.475-485
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• 2009

In this paper a two-step algorithm is proposed to efficiently generate rebar elements from 3D CAD data in the context of CAD/CAE data transfer. The first step is an algorithm to identify various type rebar objects and their attributes by analyzing 3D CAD data in STEP format, which is one of the international data standards. The second algorithmic step is a procedure to generate one-dimensional rebar elements from the object data made through the first step for finite element analysis or other CAE tasks. Successful rebar element data generation from real 3D CAD data for a reinforced concrete structure shows the efficacy of the proposed algorithm.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.3
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• pp.179-188
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• 2015

We propose obstacle classification method based on 2D LIDAR(Light Detecting and Ranging) database. The existing obstacle classification method based on 2D LIDAR, has an advantage in terms of accuracy and shorter calculation time. However, it was difficult to classifier the type of obstacle and therefore accurate path planning was not possible. In order to overcome this problem, a method of classifying obstacle type based on width data of obstacle was proposed. However, width data was not sufficient to improve accuracy. In this paper, database was established by width, intensity, variance of range, variance of intensity data. The first classification was processed by the width data, and the second classification was processed by the intensity data, and the third classification was processed by the variance of range, intensity data. The classification was processed by comparing to database, and the result of obstacle classification was determined by finding the one with highest similarity values. An experiment using an actual autonomous vehicle under real environment shows that calculation time declined in comparison to 3D LIDAR and it was possible to classify obstacle using single 2D LIDAR.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.5
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• pp.141-148
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• 2013

There are several problems in the conventional 2-D image processing and 3-D measurement systems. In the case of the 2-D image processing system, it is not possible to detect elevation data. In a 3-D measurement system, it requires a skillful operator and a lot of time for measuring data. Also, there exist data errors depending on operators. The limitation of detecting elevation data in the 2-D image processing system can be solved by laser diodes. In this study an algorithm that measures the accurate data in a subject face to be detected by combining laser diodes and a commercial CCD camera is developed. In the development process, a planar equation is developed using laser diodes and the equation is used to obtain a normal vector. Based on the results, an algorithm that transforms commercial CCD camera coordinates to 3-D coordinates is proposed. The completed measurement method will be applied to replace a manual measurement system for vehicle bodies and parts by an automated system.

• Journal of Korean Society of Forest Science
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• v.109 no.1
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• pp.23-30
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• 2020

The use of increased computing power, machine learning, and deep learning techniques have dramatically increased in various sectors. In particular, image detection algorithms are broadly used in forestry and remote sensing areas to identify forest types and tree species. However, in South Korea, machine learning has rarely, if ever, been applied in forestry image detection, especially to classify tree species. This study integrates the application of machine learning and forest image detection; specifically, we compared the ability of two machine learning data collection methods, namely image data captured by forest experts (D1) and web-crawling (D2), to automate the classification of five trees species. In addition, two methods of characterization to train/test the system were investigated. The results indicated a significant difference in classification accuracy between D1 and D2: the classification accuracy of D1 was higher than that of D2. In order to increase the classification accuracy of D2, additional data filtering techniques were required to reduce the noise of uncensored image data.

• Cartoon and Animation Studies
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• s.48
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• pp.199-215
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• 2017

Recently, a drone is used for the general purpose application although the drone was builtfor the military purpose. A drone is actively used for the creation of contents, and an image acquisition. In this paper, we develop a 3D library module platform using 3D mesh model data, which is generated by a drone image and its point cloud. First, a lot of 2D image data are taken by a drone, and a point cloud data is generated from 2D drone images. A 3D mesh data is acquired from point cloud data. Then, we develop a service library platform using a transformed 3D data for multi-purpose uses. Our platform with 3D data can minimize the cost and time of contents creation for special effects during the production of a movie, drama, or documentary. Our platform can contribute the creation of experts for the digital contents production in the field of a realistic media, a special image, and exhibitions.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.5
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• pp.330-337
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• 2022

Research on object detection algorithms using 2D data has already progressed to the level of commercialization and is being applied to various manufacturing industries. Object detection technology using 2D data has an effective advantage, there are technical limitations to accurate data generation and analysis. Since 2D data is two-axis data without a sense of depth, ambiguity arises when approached from a practical point of view. Advanced countries such as the United States are leading 3D data collection and research using 3D laser scanners. Existing processing and detection algorithms such as ICP and RANSAC show high accuracy, but are used as a processing speed problem in the processing of large-scale point cloud data. In this study, PointNet a representative technique for detecting objects using widely used 3D point cloud data is analyzed and described. And RandLA-Net, which overcomes the limitations of PointNet's performance and object prediction accuracy, is described a review of detection technology using point cloud data was conducted.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.9
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• pp.991-999
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• 2013

Lower limbs deformity is a congenital disease and can also be occurred by an acquired factor. This paper suggests a new technique for surgical planning of Corrective Osteotomy for Lower Limbs (COLL) using 2D-3D medical image registration. Converting to a 3D modeling data of lower limb based on CT (computed tomography) scan, and divide it into femur, tibia and fibula; which composing the lower limb. By rearranging the model based on the biplane 2D images of X-ray data, a 3D upright bone structure was acquired. There are two ways to array the 3D data on the 2D image: Intensity-based registration and feature-based registration. Even though registering Intensity-based method takes more time, this method will provide more precise results, and will improve the accuracy of surgical planning.