• Journal of KIISE:Computer Systems and Theory
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• v.31 no.3_4
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• pp.247-256
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• 2004

This paper presents an efficient collision detection algorithm the performance of which is independent of animation speed. Most of the previous collision detection algorithms are incremental and discrete methods, which find out the neighborhood of the extreme vertex at the previous time instance in order to get an extreme vertex at each time instance. However, if an object collides with another one with a high torque, then the angular speed becomes faster. Hence, the candidate by the incremental algorithms may be farther from the real extreme vertex at this time instance. Therefore, the worst time complexity nay be $O(n^2)$, where n is the number of faces. Moreover, the total time complexity of incremental algorithms is dependent on the time step size of animation because a smaller time step yields more frequent evaluation of Euclidean distance. In this paper, we propose a new method to overcome these drawbacks. We construct a spherical extreme vertex diagram on Gauss Sphere, which has geometric properties, and then generate the distance function of a polyhedron and a plane by using this diagram. In order to efficiently compute the exact collision time, we apply the interval Newton method to the distance function.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.4 s.310
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• pp.103-112
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• 2006

In this paper, we propose a PC based immersive virtual environment system with expandability and compatibility in contrary to existing immersive virtual environment(IVE) systems which have been implemented by supercomputer or special computing system. The application based on commercial personal compute may have two major advantage: one is variety of resources, the other is user-friendly interface. This system intends to offer easy contact to IVE system, realistic images, and convenience. Also, the system can handle various virtual reality at real-time and make it easier to interface existing complicated haptic device. Geometric techniques are adopted to calculate and visualize the physical phenomenon to speed up the computing time. The proposed implementation method of PC based immersive virtual environment system is implemented to the example in which user move around inside of and interact with virtual office environment wearing data glove, behavior recognition devices, and HMD.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.9
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• pp.1057-1063
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• 2007

To analyze the performance of mobile communication systems, the exact information of the carrier-to-interference ratio is important. Under the presence of an interferer in a cell, the carrier-to-interference ratio of the receiver is determined by the ratio between the informer-receiver distance$(d_0)$ and the receiver-interferer distance$(d_1)$. In this paper, we derive the carrier-to-interference distribution based on $d_0/d_1$ values using the geometric relation among the informer, interferer and receiver, and confirm its exactness using the simulation result. We also apply the derivation result to a system with the adjacent channel interference, and analyze the outage probability.

• Korean Journal of Digital Imaging in Medicine
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• v.10 no.1
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• pp.21-28
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• 2008

Diagnostic display monitor QA according to AAPM TG18 is usually performed by PACS administrator, product manager and reading doctor, and for acceptance testing and periodic quality control evaluation, a combination of visual and quantitative tests can be used, as outlined in sections 5 and 6 of 'assessment of display performance for medical imaging systems'. Although many display tests can be performed visually, a more objective and quantitative evaluation of display performance requires special test tools. The required instruments vary in their complexity and cost, depending on the context of the evaluation(research, acceptance testing, or quality control) and how thorough the evaluation needs to be. Objective and reliable assessment of many display characteristics can be performed with relatively inexpensive equipment, So, we made 'AAPM TG18 guiding instrument' to ues variable purpose of the evaluation of 'geometrical distortions(quantitative"', 'veiling glare(visual)' and 'sensor calibration'. The spatial measurements for the quantitative evaluation of geometric distortions, and the measurement of the veling-glare ring response function which provides information regarding the spatial extent of the luminance spread, can be performed using the TG18 guiding instrument can be used to sensor calibration to standardize the basic rate of 0% luminance when periodic calibration.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.5_6
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• pp.319-323
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• 2003

Let P be a set of n points in the plane. A minimum spanning tree(MST) is a spanning tree connecting n points of P such that the sum of lengths of edges of the tree is minimized. A diameter of a tree is the maximum length of paths connecting two points of a spanning tree of P. The problem considered in this paper is to compute the spanning tree whose diameter is minimized over all spanning trees of P. We call such tree a minimum-diameter spanning tree(MDST). The best known previous algorithm[3] finds MDST in $O(n^2)$ time. In this paper, we suggest an approximation algorithm to compute a spanning tree whose diameter is no more than 5/4 times that of MDST, running in O(n$^2$log$^2$n) time. This is the first approximation algorithm on the MDST problem.

• Korean Journal of Remote Sensing
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• v.26 no.4
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• pp.439-449
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• 2010

This paper reports experiments and analysis work done to find out the cause of Y parallex for stereo pairs of KOMPSAT-2 images and means to improve the Y parallex problem. We could conclude that the Y parallex problem was caused by resampling errors of KOMPSAT-2 PANchromatic bands, induced by the process of warping PANchromatic band with reference to multispectral bands. We could also conclude that a rigorous warping process could improve resampling of KOMPSAT-2 PANchromatic band and remove the Y parallex problem significantly. We also confirmed that a rigorous warping process could also remove blocky brightness patterns present on KOMPSAT-2 PANchromatic band. Therefore, by implementing more rigorous warping process within KOMPSAT-2 scene generation procedures, KOMPSAT-2 geometric and radiometric quality will be improved.

• Steel and Composite Structures
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• v.44 no.1
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• pp.33-47
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• 2022

This paper presents a finite element model for predicting the monotonic behaviour of bolted endplate joints connecting steel-concrete composite walls and steel beams. The demountable Hollo-bolts are utilised to facilitate the quick installation and dismantling for replacement and reuse. In the developed model, material and geometric nonlinearities were included. The accuracy of the developed model was assessed by comparing the numerical results with previous experimental tests on hollow/composite column-to-steel beam joints that incorporated endplates and Hollo-bolts. In particular, the Hollo-bolts were modelled with the expanded sleeves involved, and different material properties of the Hollo-bolt shank and sleeves were considered based on the information provided by the manufacture. The developed models, therefore, can be applied in the present study to simulate the wall-to-beam joints with similar structural components and characteristics. Based on the validated model, the authors herein compared the behaviour of wall-to-beam joints of two commonly utilised composite walling systems (Case 1: flat steel plates with headed studs; Case 2: lipped channel section with partition plates). Considering the ease of manufacturing, onsite erection and the pertinent costs, composite walling system with flat steel plates and conventional headed studs (Case 1) was the focus of present study. Specifically, additional headed studs were pre-welded inside the front wall plates to enhance the joint performance. On this basis, a series of parametric studies were conducted to assess the influences of five design parameters on the behaviour of bolted endplate wall-to-beam joints. The initial stiffness, plastic moment capacity, as well as the rotational capacity of the composite wall-to-beam joints based on the numerical analysis were further compared with the current design provision.

• Smart Structures and Systems
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• v.29 no.1
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• pp.29-39
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• 2022

Crack detection plays an important role in the maintenance and protection of steel box girder of bridges. However, since the cracks only occupy an extremely small region of the high-resolution images captured from actual conditions, the existing methods cannot deal with this kind of image effectively. To solve this problem, this paper proposed a novel three-stage method based on deep learning technology and morphology operations. The training set and test set used in this paper are composed of 360 images (4928 × 3264 pixels) in steel girder box. The first stage of the proposed model converted high-resolution images into sub-images by using patch-based method and located the region of cracks by CBAM ResNet-50 model. The Recall reaches 0.95 on the test set. The second stage of our method uses the Attention U-Net model to get the accurate geometric edges of cracks based on results in the first stage. The IoU of the segmentation model implemented in this stage attains 0.48. In the third stage of the model, we remove the wrong-predicted isolated points in the predicted results through dilate operation and outlier elimination algorithm. The IoU of test set ascends to 0.70 after this stage. Ablation experiments are conducted to optimize the parameters and further promote the accuracy of the proposed method. The result shows that: (1) the best patch size of sub-images is 1024 × 1024. (2) the CBAM ResNet-50 and the Attention U-Net achieved the best results in the first and the second stage, respectively. (3) Pre-training the model of the first two stages can improve the IoU by 2.9%. In general, our method is of great significance for crack detection.

• Current Optics and Photonics
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• v.7 no.3
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• pp.237-247
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• 2023

In middle- and long-distance imaging systems, due to the atmospheric turbulence caused by temperature, wind speed, humidity, and so on, light waves propagating in the air are distorted, resulting in image-quality degradation such as geometric deformation and fuzziness. In remote sensing, astronomical observation, and traffic monitoring, image information loss due to degradation causes huge losses, so effective restoration of degraded images is very important. To restore images degraded by atmospheric turbulence, an image-restoration method based on improved compound multibranch feature fusion (CMFNetPro) was proposed. Based on the CMFNet network, an efficient channel-attention mechanism was used to replace the channel-attention mechanism to improve image quality and network efficiency. In the experiment, two-dimensional random distortion vector fields were used to construct two turbulent datasets with different degrees of distortion, based on the Google Landmarks Dataset v2 dataset. The experimental results showed that compared to the CMFNet, DeblurGAN-v2, and MIMO-UNet models, the proposed CMFNetPro network achieves better performance in both quality and training cost of turbulent-image restoration. In the mixed training, CMFNetPro was 1.2391 dB (weak turbulence), 0.8602 dB (strong turbulence) respectively higher in terms of peak signal-to-noise ratio and 0.0015 (weak turbulence), 0.0136 (strong turbulence) respectively higher in terms of structure similarity compared to CMFNet. CMFNetPro was 14.4 hours faster compared to the CMFNet. This provides a feasible scheme for turbulent-image restoration based on deep learning.

• Current Optics and Photonics
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• v.8 no.3
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• pp.215-224
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• 2024

In medium- and long-range optical imaging systems, atmospheric turbulence causes blurring and distortion of images, resulting in loss of image information. An image-restoration method based on an adaptive feature-fusion multi-input-multi-output (MIMO) dense U-shaped network (Unet) is proposed, to restore a single image degraded by atmospheric turbulence. The network's model is based on the MIMO-Unet framework and incorporates patch-embedding shallow-convolution modules. These modules help in extracting shallow features of images and facilitate the processing of the multi-input dense encoding modules that follow. The combination of these modules improves the model's ability to analyze and extract features effectively. An asymmetric feature-fusion module is utilized to combine encoded features at varying scales, facilitating the feature reconstruction of the subsequent multi-output decoding modules for restoration of turbulence-degraded images. Based on experimental results, the adaptive feature-fusion MIMO dense U-shaped network outperforms traditional restoration methods, CMFNet network models, and standard MIMO-Unet network models, in terms of image-quality restoration. It effectively minimizes geometric deformation and blurring of images.