• Journal of the Korean Society for Precision Engineering
• /
• v.30 no.6
• /
• pp.601-606
• /
• 2013

3D scanning is a technique to measure the 3D shape information of the object. Shape information obtained by 3D scanning is expressed either as point cloud or as polygon mesh type data that can be widely used in various areas such as reverse engineering and quality inspection. 3D scanning should be performed as accurate as possible since the scanned data is highly required to detect the features on an object in order to scan the shape of the object more precisely. In this study, we propose the method on finding the location of feature more accurately, based on the extended Biplane SNAKE with global optimization. In each iteration, we project the feature lines obtained by the extended Biplane SNAKE into each image plane and move the feature lines to the features on each image. We have applied this approach to real models to verify the proposed optimization algorithm.

• Korean Journal of Construction Engineering and Management
• /
• v.25 no.3
• /
• pp.68-82
• /
• 2024

The planning stage of laser scanning is crucial for acquiring high-quality 3D source data. It involves assessing the target space's environment and formulating an effective measurement strategy. However, existing practices often overlook on-site conditions, with decisions on scanner deployment and scanning locations relying heavily on the operators' experience. This approach has resulted in frequent modifications to scanning locations and diminished 3D data quality. Previous research has explored the selection of optimal scanner locations and conducted preliminary reviews through simulation, but these methods have significant drawbacks. They fail to consider scanner inaccuracies, do not support the use of multiple scanners, rely on less accurate 2D drawings, and require specialized knowledge in 3D modeling and programming. This study introduces an optimization technique for laser scanning planning using 3D simulation to address these issues. By evaluating the accuracy of scan data from various laser scanners and their positioning for scanning a retaining wall structure in a small-scale building, this method aids in refining the laser scanning plan. It enhances the decision-making process for end-users by ensuring data quality and reducing the need for plan adjustments during the planning phase.

• The KIPS Transactions:PartD
• /
• v.11D no.2
• /
• pp.247-258
• /
• 2004

Recently, there have been researches on storage and retrieval technique of moving objects, which are highly concerned by user in database application area such as video databases, spatio-temporal databases, and mobile databases. In this paper, we propose a new signature-based indexing scheme which supports similar sub-trajectory retrieval at well as good retrieval performance on moving objects trajectories. Our signature-based indexing scheme is classified into concatenated signature-based indexing scheme for similar sub-trajectory retrieval, entitled CISR scheme and superimposed signature-based indexing scheme for similar sub-trajectory retrieval, entitled SISR scheme according to generation method of trajectory signature based on trajectory data of moving object. Our indexing scheme can improve retrieval performance by reducing a large number of disk access on data file because it first scans all signatures and does filtering before accessing the data file. In addition, we can encourage retrieval efficiency by appling k-warping algorithm to measure the similarity between query trajectory and data trajectory. Final]y, we evaluate the performance on sequential scan method(SeqScan), CISR scheme, and SISR scheme in terms of data insertion time, retrieval time, and storage overhead. We show from our experimental results that both CISR scheme and SISR scheme are better than sequential scan in terms of retrieval performance and SISR scheme is especially superior to the CISR scheme.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.12
• /
• pp.505-518
• /
• 2023

3D point cloud semantic segmentation is a computer vision task that involves dividing the point cloud into different objects and regions by predicting the class label of each point. Existing 3D semantic segmentation models have some limitations in performing sufficient fusion of multi-modal features while ensuring both characteristics of 2D visual features extracted from RGB images and 3D geometric features extracted from point cloud. Therefore, in this paper, we propose MMCA-Net, a novel 3D semantic segmentation model using 2D-3D multi-modal features. The proposed model effectively fuses two heterogeneous 2D visual features and 3D geometric features by using an intermediate fusion strategy and a multi-modal cross attention-based fusion operation. Also, the proposed model extracts context-rich 3D geometric features from input point cloud consisting of irregularly distributed points by adopting PTv2 as 3D geometric encoder. In this paper, we conducted both quantitative and qualitative experiments with the benchmark dataset, ScanNetv2 in order to analyze the performance of the proposed model. In terms of the metric mIoU, the proposed model showed a 9.2% performance improvement over the PTv2 model using only 3D geometric features, and a 12.12% performance improvement over the MVPNet model using 2D-3D multi-modal features. As a result, we proved the effectiveness and usefulness of the proposed model.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.38 no.4
• /
• pp.427-439
• /
• 2014

This study identifies the foot side shapes of elderly men by classifying foot types according to 3D foot shapes and analyzing individual characteristics. The subjects were 284 elderly men over 60 years of age who lived in Gwangju and did not have foot related diseases. They were measured with a scanner (Nexcan$^{(R)}$ of K&I Technology) to obtain three dimensional feet shapes. Anthropometric measuring items consisted of 28 items estimated on the right foot of each subject. 3D scan data were analyzed by various statistical methods such as factor analysis, ANOVA and cluster analysis using the statistical program SPSS 19.0. A total of 7 factors were extracted through a factor analysis and these factors represent 77.56% of total variance. The 8 factors were: inside height and side gradient, ankle thickness, size from foot center to ankle, lateral malleolus height, forefoot height, instep and heel height and gradient. A total of 3 clusters (as foot type) were categorized using 7 factor scores by cluster analysis. Type 1 was classified as high forefoot and low midfoot compared to the length. Type 2 was classified as low forefoot and high midfoot, and type 3 was classified as low forefoot and low midfoot.

• Atmosphere
• /
• v.23 no.4
• /
• pp.453-470
• /
• 2013

As a part of the KIAPS Observation Processing System (KOPS), we have developed the modules of satellite radiance data pre-processing and quality control, which include observation operators to interpolate model state variables into radiances in observation space. AMSU-A (Advanced Microwave Sounding Unit-A) level-1d radiance data have been extracted using the BUFR (Binary Universal Form for the Representation of meteorological data) decoder and a first guess has been calculated with RTTOV (Radiative Transfer for TIROS Operational Vertical Sounder) version 10.2. For initial quality checks, the pixels contaminated by large amounts of cloud liquid water, heavy precipitation, and sea ice have been removed. Channels for assimilation, rejection, or monitoring have been respectively selected for different surface types since the errors from the skin temperature are caused by inaccurate surface emissivity. Correcting the bias caused by errors in the instruments and radiative transfer model is crucial in radiance data pre-processing. We have developed bias correction modules in two steps based on 30-day innovation statistics (observed radiance minus background; O-B). The scan bias correction has been calculated individually for each channel, satellite, and scan position. Then a multiple linear regression of the scan-bias-corrected innovations with several predictors has been employed to correct the airmass bias.

• The Journal of Korean Society for Radiation Therapy
• /
• v.33
• /
• pp.47-54
• /
• 2021

Purpose : In order to evaluate the usefulness of clinical application of the Pause & Resume methods by comparing and analyzing the data stability and dose reduction effect when repeat scan assuming irregular breathing and using the Pause & Resume method during chest 4D CT using Quasar^TM Phantom. Materials and Methods : Using the Quasar^TM Phantom, set the breathing rate per minute to 15 BPM and 7.5 BPM, and set the S15 point as an irregular breathing section, and then placed OSLD to this point and use the Pause & Resume method to measure the dose of S15. CTDIvol, DLP, and ALARA-CT were used for comparative analysis of radiation dose between Pause & Resume method and Repeat-scan. In order to evaluate the stability and usability of the data applying the Pause & Resume method, the captured images were sorted by Advanced Workstation Volume Share7 and then sent to Eclipse^TM, the diameter and volume were analyzed by forming a contour on the iron ball in the Quasar^TM Phantom Results : When using Pause & Resume, the dose of OSLD measurement increased by 1.97 times in the section of S15. As a result of image evaluation, the average value of all volumes measured with and without the Pause & Resume method at 15 BPM and 7.5 BPM was 15.2 cm3±0.5%.Allthemeasuredvaluesfor the radius of iron ball were 3.1 cm regardless of whether Pause & Resume method was used or not. In the case of using Pause & Resume, 33% decreased from the lowest DLP value and 38% decreased from the highest DLP value of repeat scan, and the effective dose also decreased 32.1% from the minimum value and 37.6% from the maximum value. Conclusion: Irradiation dose was increased by Pause & Resume method because of the repeat scan on the S15 site where assuming irregular breathing occurred, However Pause & Resume method led to a significant reduction in dose on overall scan range. It also proved the usefulness of clinical application of the Pause & Resume method as a result of similar diameters and volumes of iron ball measurement.

• Investigative Magnetic Resonance Imaging
• /
• v.14 no.1
• /
• pp.56-63
• /
• 2010

Purpose : DIR image is relatively free from susceptibility artifacts therefore, DIR image can make it possible to reliably measure cortical thickness/volume. One drawback of the DIR acquisition is the long scan time to acquire the fully sampled 3D data set. To solve this problem, we applied a parallel imaging method (GRAPPA) and verify the reliability of using the volumetric study. Materials and methods : Six healthy volunteers (3 males and 3 females; age $25.33{\pm}2.25$ years) underwent MRI using the 3D DIR sequence at a 3.0T Siemens Tim Trio MRI scanner. GRAPPA simulation was performed from the fully sampled data set for reduction factor 2. Data reconstruction was performed using MATLAB R2009b. Freesurfer v.4.3.0 was used to evaluate the cortical thickness of the entire brain, and to extract white matter information from the DIR image, Analyze 9.0 was used. The global cortical thickness estimated from the reconstructed image was compared with reference image by using a T-test in SPSS. Results : Although reduced SNR and blurring are observed from the reconstructed image, in terms of segmentation the effect was not so significant. The volumetric result was validated that there were no significant differences in many cortical regions. Conclusion : This study was performed with DIR image for a volumetric MRI study. To solve the long scan time of 3D DIR imaging, we applied GRAPPA algorithm. According to the results, fast imaging can be done with reduction factor 2 with little loss of image quality at 3.0T.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.30 no.8
• /
• pp.1242-1252
• /
• 2006

Many applications in computer graphics require complex, highly detailed models. However, to control processing time, it is often desirable to use approximations in place of excessively detailed models. Therefore, we have developed the notion of an optimal matrix to simplify the model surface which can then rapidly obtain high quality 2D patterns by flattening the 3D surface. Firstly, the woman's 3D body was modeled based on Size Korea data. Secondly, the 3D model was divided by shell and block for the pattern draft. Thirdly, each block was flattened by the grid and bridge method. Finally, we select the optimal matrix and demonstrate it's efficiency and quality. The proposed approach accommodates surfaces with darts, which are commonly utilized in the clothing industry to reduce the deformation of surface forming and flattening. The resulting optimal matrix could be an initiation of standardization for pattern flattening. This can facilitate much better approximations, in both efficiency and exactness.

• Korean Journal of Remote Sensing
• /
• v.34 no.6_1
• /
• pp.847-855
• /
• 2018

GMTI (Ground Moving Target Indicator) is a kind of airborne radar function that is used widely in military applications to detect the moving targets on the ground. In this paper, GMTI signal processing technique was presented and its performance was verified using sum and difference channels raw data obtained by the captive flight test.