• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.582-585
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• 2014

Visualization is a science which makes the invisible to visible through the techniques of experimental visualization and computer-aided visualization. This paper presents the practical aspects of visualization of multivariate dataset. In this paper, we will briefly discuss a previous research work and introduce a new visualization technique which will help us to design and develop a visualization tool for experimental visualization of multivariate dataset. Our newly developed visualization tool can be used in various domains. In this paper, we have chosen a software industry as an application domain and we used the multivariate dataset of software components computed by VizzMaintenance. VizzMaintenance is software analysis tool which give us multiple software metrics of open source Java based programs. Main objective of this research is to develop a new visualization tool for large multivariate dataset which will be more efficient and easy to perceive by viewer. Perception is very important for our research work and we have decided to test the perception level of our proposed visualization approach by researchers of our research lab.

• Journal of Korea Game Society
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• v.8 no.3
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• pp.61-68
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• 2008

Quadtree-based terrain visualization methods have been used in a lot of applications. However, because most procedures are performed on the CPU, the rendering speed is slow in comparison to methods using GPU. In this paper, we present a quadtree-based terrain visualization method working on the GPU with specially designed data structure, error-texture and LOD-texture, and block-based acceleration method. In preprocessing step, we calculate errors in world space and store them to error-texture. In rendering step, we examine projected errors of error-texture and choose the detail level, then store the projected errors to LOD-texture. View frustum culling is performed as block unit using the values of error-texture and LOD-texture. This method reduces CPU load and performs time consuming jobs such as LOD selection and view frustum culling.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.63-70
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• 2009

3D GIS(Geographic Information System) processes, analyzes and presents various real-world 3D phenomena by building 3D spatial information of real-world terrain, facilities, etc., and working with visualization technique such as VR(Virtual Reality). It can be applied to such areas as urban management system, traffic information system, environment management system, disaster management system, ocean management system, etc,. In this paper, we propose video visualization technology based on 3D geographic information to provide effectively real-time information in 3D geographic information system and also present methods for establishing 3D building information data. The proposed video visualization system can provide real-time video information based on 3D geographic information by projecting real-time video stream from network video camera onto 3D geographic objects and applying texture-mapping of video frames onto terrain, facilities, etc.. In this paper, we developed sem i-automatic DBM(Digital Building Model) building technique using both aerial im age and LiDAR data for 3D Projective Texture Mapping. 3D geographic information system currently provide static visualization information and the proposed method can replace previous static visualization information with real video information. The proposed method can be used in location-based decision-making system by providing real-time visualization information, and moreover, it can be used to provide intelligent context-aware service based on geographic information.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.69-72
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• 1996

A new flow visualization image processing technique was studied. Our approach is based on texture fields and has higher performance than similar methods. We tested our method to flow visualization of Total Artificial Heart.

• Journal of the Korea Computer Graphics Society
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• v.7 no.2
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• pp.21-28
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• 2001

As a result of the recent explosive growth of scientific data, extremely large volume datasets have become increasingly commonplace. While several texture-based volume rendering algorithms have been proposed, most of them focused on volumes smaller than the hardware's available texture memory. This paper presents a new parallel volume rendering scheme for very large static and time-varying data on a multipipe system architecture. Our scheme subdivides large volumes dynamically into smaller bricks, and assigns them adaptively to graphics pipes to minimize the costs of texture swapping. With the new method, Phong shaded images can be easily created by computing the gradients on the fly and using the color matrix feature of OpenGL. We report experimental results on an SGI Onyx2 for the various large datasets.

• Journal of Korea Multimedia Society
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• v.11 no.5
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• pp.623-632
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• 2008

In this paper, we used the color transfer function and the opacity transfer function for the internal 3D object visualization of an image volume data. In transfer function, creating values of between boundaries generally is ambiguous. We concentrated to extract boundary features for segmenting the visual volume rendering objects. Consequently we extracted an image gradient feature in spatial domain and created a multi-dimensional transfer function according to the GPU efficient improvement. Finally using these functions we obtained a good research result as an implementing object boundary visualization of the graphic hardware based 3D texture mapping.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.311-326
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• 2024

The rapid development of neural network technology promotes the neural network model driven by big data to overcome the texture effect of complex objects. Due to the limitations in complex scenes, it is necessary to establish custom template matching and apply it to the research of many fields of computational vision technology. The dependence on high-quality small label sample database data is not very strong, and the machine learning system of deep feature connection to complete the task of texture effect inference and speculation is relatively poor. The style transfer algorithm based on neural network collects and preserves the data of patterns, extracts and modernizes their features. Through the algorithm model, it is easier to present the texture color of patterns and display them digitally. In this paper, according to the texture effect reasoning of custom template matching, the 3D visualization of the target is transformed into a 3D model. The high similarity between the scene to be inferred and the user-defined template is calculated by the user-defined template of the multi-dimensional external feature label. The convolutional neural network is adopted to optimize the external area of the object to improve the sampling quality and computational performance of the sample pyramid structure. The results indicate that the proposed algorithm can accurately capture the significant target, achieve more ablation noise, and improve the visualization results. The proposed deep convolutional neural network optimization algorithm has good rapidity, data accuracy and robustness. The proposed algorithm can adapt to the calculation of more task scenes, display the redundant vision-related information of image conversion, enhance the powerful computing power, and further improve the computational efficiency and accuracy of convolutional networks, which has a high research significance for the study of image information conversion.

• Journal of IKEEE
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• v.24 no.1
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• pp.254-259
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• 2020

This paper is the implementation of the conversion system from image to music based on intentional synesthesia. The input image based on color, texture, and shape was converted into melodies, harmonies and rhythms of music, respectively. Depending on the histogram of colors, the melody can be selected and obtained probabilistically to form the melody. The texture in the image expressed harmony and minor key with 7 characteristics of GLCM, a statistical texture feature extraction method. Finally, the shape of the image was extracted from the edge image, and using Hough Transform, a frequency component analysis, the line components were detected to produce music by selecting the rhythm according to the distribution of angles.

• Journal of Korea Multimedia Society
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• v.18 no.1
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• pp.65-70
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• 2015

Particle accelerator has mainly used in nuclear field only because of the large scale of the facility. However, since laser-plasma particle accelerator which has smaller size and spends less cost developed, the availability of this accelerator is expended to various research fields such as industrial and medical. This paper suggests a visualization system to control the laser-plasma particle accelerator efficiently. This system offers real-time 3D images via convert HDF file comes from plasma data obtained from PIC simulation into OpenGL texture type to analyse and modify plasma data. After that, it stores high-resolution rendering images of the data with external renderer hereafter.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.6
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• pp.679-691
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• 2002

Volume visualization is an important subarea of scientific visualization, and is concerned with techniques that are effectively used in generating meaningful and visual information from abstract and complex volume datasets, defined in three- or higher-dimensional space. It has been increasingly important in various fields including meteorology, medical science, and computational fluid dynamics, and so on. On the other hand, virtual reality is a research field focusing on various techniques that aid gaining experiences in virtual worlds with visual, auditory and tactile senses. In this paper, we have developed a visualization system for CAVE, an immersive 3D virtual environment system, which generates stereoscopic images from huge human volume datasets in real-time using an improved volume visualization technique. In order to complement the 3D texture-mapping based volume rendering methods, that easily slow down as data sizes increase, our system utilizes an image-based rendering technique to guarantee real-time performance. The system has been designed to offer a variety of user interface functionality for effective visualization. In this article, we present detailed description on our real-time stereoscopic visualization system, and show how the Visible Korean Human dataset is effectively visualized on CAVE.