• The Mathematical Education
• /
• v.53 no.4
• /
• pp.493-507
• /
• 2014

The purpose of this study is to analyze how high school students form and interpret the mental image in the process of solving regular polyhedron problems. For this purpose, a set of problems about the regular polyhedron's vertex is developed on the base of the regular polyhedron's duality and circulation. and applied to 2 students of the 12th graders in D high school. After 2 hours of teaching and learning and another 2 hours of mental image-analysis process, the following research findings are obtained. Fisrt, a student who recorded medium high-level grade in the national scholastic test can build the dynamic image or the patten image in the process of solving regular polyhedron's vertex problems by utilizing the 3D geometry program. However, the other student who recorded low-level grade can build the concrete-pictorial image. Second, pattern image or dynamic image can help students solve the regular polyhedron's vertex problems by proper transformation of informations and the mental images while the concrete-pictorial image does not help. Hence, it is recommended that the mathematics teachers should develop teaching and learning materials about the regular polyhedron's duality and circulation and also give students suitable questions to build the various mental images.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.6
• /
• pp.797-803
• /
• 2014

In this paper, 3D face recognition system is designed by using polynomial based on RBFNNs. In case of 2D face recognition, the recognition performance reduced by the external environmental factors such as illumination and facial pose. In order to compensate for these shortcomings of 2D face recognition, 3D face recognition. In the preprocessing part, according to the change of each position angle the obtained 3D face image shapes are changed into front image shapes through pose compensation. the depth data of face image shape by using Multiple Point Signature is extracted. Overall face depth information is obtained by using two or more reference points. The direct use of the extracted data an high-dimensional data leads to the deterioration of learning speed as well as recognition performance. We exploit principle component analysis(PCA) algorithm to conduct the dimension reduction of high-dimensional data. Parameter optimization is carried out with the aid of PSO for effective training and recognition. The proposed pattern classifier is experimented with and evaluated by using dataset obtained in IC & CI Lab.

• Journal of Korea Multimedia Society
• /
• v.20 no.11
• /
• pp.1820-1827
• /
• 2017

With the development of 3D technology, image expression has been widely used in the field of 3D animation these days for the purpose of illustrating a certain image, feeling or status. In this paper, we examine how it affects to audiences' feelings and senses when we applied the handheld camera technique to other kinetic characteristics. In addition, we analyze the scenes which the handheld camera technique is applied into each characteristic from movie contents, present the kinetic characteristics of the handheld camera technique, and study the scenes that can apply this technique with 3D animation and its influence.

• Journal of radiological science and technology
• /
• v.42 no.1
• /
• pp.53-59
• /
• 2019

In the field of nuclear medicine, the various static phantoms of international standards are used to assess the performance of the nuclear medicine equipment. However, we only reproduced a fixed situation in spite of the movement of the cardiac, and the demands for dynamic situations have been continuously raised. More research is necessary to address these challenges. This study used flexible materials to design the dynamic cardiac phantom, taking into account the various clinical situations. It also intended to reproduce the images through dynamic cardiac flow to confirm the usefulness of the proposed technique. The frame of dynamic cardiac phantom was produced based on the international standard phantom. A nuclear medicine dynamic cardiac phantom was produced rubber material and silicone implemented by 3D printing technique to reproduce endocardium and epicardium movement. Therefore we compared and evaluated the image of a cardiac phantom made of rubber material and a cardiac phantom made of silicone material by 3D printing technique. According to the results of this study, the analysis of the Summed Rest Score(SRS) showed abnormalities in the image of a cardiac phantom made of rubber material at 10, 20, and 30 stroke rates, but the image of a cardiac phantom made of silicone material by 3D printing technique showed normal levels. And the analysis of the Total Perfusion Deficit(TPD) showed that TPD in the image of a cardiac phantom made of rubber material was higher than that of the image of a cardiac phantom made of silicone material by 3D printing technique at 10, 20, and 30 stroke rates. The potential for clinical application of the proposed method was confirmed in the dynamic cardiac phantom implemented with 3D printing technique. It is believed that the objective information secures the reliability of inspection equipment and it contributes to improve the diagnostic value of nuclear medicine.

• Electronics and Telecommunications Trends
• /
• v.35 no.5
• /
• pp.112-122
• /
• 2020

In 3D computer graphics, a depth map is an image that provides information related to the distance from the viewpoint to the subject's surface. Stereo sensors, depth cameras, and imaging systems using an active illumination system and a time-resolved detector can perform accurate depth measurements with their own light sources. The 3D image information obtained through the depth map is useful in 3D modeling, autonomous vehicle navigation, object recognition and remote gesture detection, resolution-enhanced medical images, aviation and defense technology, and robotics. In addition, the depth map information is important data used for extracting and restoring multi-view images, and extracting phase information required for digital hologram synthesis. This study is oriented toward a recent research trend in deep learning-based 3D data analysis methods and depth map information extraction technology using a convolutional neural network. Further, the study focuses on 3D image processing technology related to digital hologram and multi-view image extraction/reconstruction, which are becoming more popular as the computing power of hardware rapidly increases.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.8 no.1
• /
• pp.191-197
• /
• 2013

Conventional CT and MRI scans produce cross-section slices of body that are viewed sequentially by radiologists who must imagine or extrapolate from these views what the 3 dimensional anatomy should be. By using sophisticated algorithm and high performance computing, these cross-sections may be rendered as direct 3D representations of human anatomy. The 2D medical image analysis forced to use time-consuming, subjective, error-prone manual techniques, such as slice tracing and region painting, for extracting regions of interest. To overcome the drawbacks of 2D medical image analysis, combining with medical image processing, 3D visualization is essential for extracting anatomical structures and making measurements. We used the gray-level thresholding, region growing, contour following, deformable model to segment human organ and used the feature vectors from texture analysis to detect harmful cancer. We used the perspective projection and marching cube algorithm to render the surface from volumetric MR and CT image data. The 3D visualization of human anatomy and segmented human organ provides valuable benefits for radiation treatment planning, surgical planning, surgery simulation, image guided surgery and interventional imaging applications.

• Proceedings of the Korean Society of Medical Physics Conference
• /
• 2002.09a
• /
• pp.121-122
• /
• 2002

The main principle of radiation therapy is to deliver optimum dose to tumor to increase tumor cure probability while minimizing dose to critical normal structure to reduce complications. RTP system is required for proper dose plan in radiation therapy treatment. The main goal of this research is to develop dose model for photon, electron, and brachytherapy, and to display dose distribution on patient images with optimum process. The main items developed in this research includes: (l) user requirements and quality control; analysis of user requirement in RTP, networking between RTP and relevant equipment, quality control using phantom for clinical application (2) dose model in RTP; photon, electron, brachytherapy, modifying dose model (3) image processing and 3D visualization; 2D image processing, auto contouring, image reconstruction, 3D visualization (4) object modeling and graphic user interface; development of total software structure, step-by-step planning procedure, window design and user-interface. Our final product show strong capability for routine and advance RTP planning.

• Korean Journal of Remote Sensing
• /
• v.35 no.6_1
• /
• pp.959-971
• /
• 2019

CNN (Convolutional Neural Network) is one representative deep learning algorithm, which can extract high-level spatial and spectral features, and has been applied for hyperspectral image classification. However, one significant drawback behind the application of CNNs in hyperspectral images is the high dimensionality of the data, which increases the training time and processing complexity. To address this problem, several CNN based hyperspectral image classification studies have exploited PCA (Principal Component Analysis) for dimensionality reduction. One limitation to this is that the spectral information of the original image can be lost through PCA. Although it is clear that the use of PCA affects the accuracy and the CNN training time, the impact of PCA for CNN based hyperspectral image classification has been understudied. The purpose of this study is to analyze the quantitative effect of PCA in CNN for hyperspectral image classification. The hyperspectral images were first transformed through PCA and applied into the CNN model by varying the size of the reduced dimensionality. In addition, 2D-CNN and 3D-CNN frameworks were applied to analyze the sensitivity of the PCA with respect to the convolution kernel in the model. Experimental results were evaluated based on classification accuracy, learning time, variance ratio, and training process. The size of the reduced dimensionality was the most efficient when the explained variance ratio recorded 99.7%~99.8%. Since the 3D kernel had higher classification accuracy in the original-CNN than the PCA-CNN in comparison to the 2D-CNN, the results revealed that the dimensionality reduction was relatively less effective in 3D kernel.

• Journal of the Semiconductor & Display Technology
• /
• v.12 no.2
• /
• pp.27-32
• /
• 2013

Shape From Focus (SFF) is a passive optical technique to recover 3D structure of an object that utilizes focus information from 2D images of the object taken at different focus levels. Mostly, SFF methods use a single focus measure to compute image focus quality of each pixel in the image sequence. However, it is difficult to recover accurate 3D shape using a single focus measure, as different focus measures perform differently in diverse conditions. In this paper, a nonlinear Total Variation (TV) based approach is proposed for 3D shape recovery. To improve the result of surface reconstruction, several initial depth maps are obtained using different focus measures and the resultant 3D shape is obtained by diffusing them through TV. The proposed method is tested and evaluated by using image sequences of synthetic and real objects. The results and comparative analysis demonstrate the effectiveness of our method.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
• /
• v.34 no.6
• /
• pp.622-627
• /
• 2008

In orthognathic surgery, precise analysis and diagnosis are essential for successful results. In facial asymmetric patient, traditional 2D image analysis has been used by lateral and P-A Cephalometric view, Skull PA, Panorama, Submentovertex view etc. But clinicians sometimes misdiagnose because they cannot find exact landmark due to superimposition, moreover image can be magnified and distorted by projection technique or patient's skull position, when using these analysis and method. For overcome these defects, analysis by using of 3D CT has been introduced. In this way we can analysis precisely by getting the exact image free of artifact and finding exact landmark with no interruption of superimposition. So we want to review of relationship between various skeletal landmarks of mandible or cranial base and facial asymmetry by predictable analysis using 3D CT. We select the cases of the patients who visited our department for correction of facial asymmetry during 2003-2007 and who were taken image of 3D CT for diagnosis. 3D CT images were reconstructed to 3D image by using V-Work program (Cybermed Inc., Seoul, Korea). And we analysis the relationship between facial asymmetry and various affecting factor of skeletal pattern. The mandibular ramus hight difference between right and left was most affecting factor that express facial asymmetry. And in this research, there was no relationship between cranial base and facial asymmetry. The angulation between facial midline and mandibular ramus divergency has significant relationship with facial asymmetry