• 한국HCI학회:학술대회논문집
• /
• 2007.02a
• /
• pp.982-987
• /
• 2007

The necessity of data compression scheme for volume data has been increased because of the increase of data capacity and the amount of network uses. Now we have various kinds of compression schemes, and we can choose one of them depending on the data types, application fields, the preferences, etc. However, the capacity of data which is produced by application scientists has been excessively increased, and the format of most scientific data is 3D volume. For 2D image or 3D moving pictures, many kinds of standards are established and widely used, but for 3D volume data, specially time-varying volume data, it is very difficult to find any applicable compression schemes. In this paper, we present a compression scheme for encoding time-varying volume data. This scheme is aimed to encoding time-varying volume data for visualization. This scheme uses MPEG's I- and P-frame concept for raising compression ratio. Also, it transforms volume data using Daubechies D4 filter before encoding, so that the image quality is better than other wavelet-based compression schemes. This encoding scheme encodes time-varying volume data composed of single precision floating-point data. In addition, this scheme provides the random reconstruction accessibility for an unit, and can be used for compressing large time-varying volume data using correlation between frames while preserving image qualities.

• Journal of Computational Design and Engineering
• /
• v.2 no.1
• /
• pp.1-15
• /
• 2015

Measured bidirectional reflectance distribution function (BRDF) data have been used to represent complex interaction between lights and surface materials for photorealistic rendering. However, their massive size makes it hard to adopt them in practical rendering applications. In this paper, we propose an adaptive method for B-spline volume representation of measured BRDF data. It basically performs approximate B-spline volume lofting, which decomposes the problem into three sub-problems of multiple B-spline curve fitting along u-, v-, and w-parametric directions. Especially, it makes the efficient use of knots in the multiple B-spline curve fitting and thereby accomplishes adaptive knot placement along each parametric direction of a resulting B-spline volume. The proposed method is quite useful to realize efficient data reduction while smoothing out the noises and keeping the overall features of BRDF data well. By applying the B-spline volume models of real materials for rendering, we show that the B-spline volume models are effective in preserving the features of material appearance and are suitable for representing BRDF data.

• Journal of Biomedical Engineering Research
• /
• v.21 no.4
• /
• pp.433-439
• /
• 2000

Volume rendering is a powerful tool for visualizing sampled scalar values from 3D data without modeling geometric primitives to the data. The volume rendering can describe the surface-detail of a complex object. Owing to this characteristic. volume rendering has been used to visualize medical data. The size of volume data is usually too big to handle in real time. Recently, various volume rendering algorithms have been proposed in order to reduce the rendering time. However, most of the proposed algorithms are not proper for fast rendering of large non-coded volume data. In this paper, we propose a block-based fast volume rendering algorithm using a shear-warp factorization for non-coded volume data. The algorithm performs volume rendering by using the organ segmentation data as well as block-based 3D volume data, and increases the rendering speed for large non-coded volume data. The proposed algorithm is evaluated by rendering 3D X-ray CT body images and MR head images.

• Korean Journal of Computational Design and Engineering
• /
• v.2 no.1
• /
• pp.11-18
• /
• 1997

Scientific volume visualization addresses the representation, manipulation, and rendering of volumetric data sets, providing mechanisms for looking closely into structures and understanding their complexity and dynamics. In the past several years, a tremendous amount of research and development has been directed toward algorithms and data modeling methods for a scientific data visualization. But there has been very little work on developing a mathematical volume model that feeds this visualization. Especially, in flow visualization, the volume model has long been required as a guidance to display the very large amounts of data resulting from numerical simulations. In this paper, we focus on the mathematical representation of volumetric data sets and the method of extracting meaningful information from the derived volume model. For this purpose, a B-spline volume is extended to a high dimensional trivariate model which is called as a flow visualization model in this paper. Two three-dimensional examples are presented to demonstrate the capabilities of this model.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2006.04a
• /
• pp.533-540
• /
• 2006

In recent years, civil-engineering work is desired the terrain information to be more efficient in earthwork volume calculation. One method for collecting elevation data is LiDAR. Lidar data was used to produce rapidly an accurate digital elevation model of the terrain, compared with the conventional ground surveys, photogrammetty, and remote sensing. Raw Lidar data is combined with GPS positional data to georeference the data sets. Lidar data is edited and processed to generate surface models, elevation models, and contours. Here we can either create a Tin Volume Surface or a Gird Volume Surface. Triangulated Irregular Network(TIN) has complex data structure, but it can describe well terrain surface features. As we have seen, we search the efficiency for earthwork volume calculation using Lidar data. One conclusion we can draw from this study is that Lidar data is more accurate result than digital map in the calculation of earthwork volume.

• KSTLE International Journal
• /
• v.6 no.1
• /
• pp.21-27
• /
• 2005

A technique for a wear volume calculation is improved and verified in this research. The wear profile data measured by a surface roughness tester is used. The present technique uses a data flattening, the FFT and the windowing procedure, which is used for a general signal processing. The measured value of an average roughness of an unworn surfnce is used for the baseline of the integration for the volume calculation. The improvements from the previous technique are the procedures of the data flattening and the determination of a baseline. It is found that the flattening procedure efnciently manipulates the raw data when the levels of it are not horizontal, which enables us to calculate the volume reasonably well and readily. By comparing it with the weight loss method by using artificial dents, the present method reveals more volume by aroung 3~10%. It is attributed to the protruded region of the specimen and the inaccuracy and data averaging during the weght loss measurement. From a thorough investigation, it is concluded that the present technique can provide an accurate wear volume.

• Transactions of the Society of Information Storage Systems
• /
• v.1 no.2
• /
• pp.143-149
• /
• 2005

In this paper we propose a novel volume hologram encryption system with binary amplitude masks rather than phase masks, in which volume holograms can be securely recorded against the attacks by a third party. In our system, the encryption is done by multiplexing two volume holograms in such a way that an original binary data page is first stored as a volume hologram by interference with a binary amplitude mask and then the complementary data page is stored as another volume hologram by interference with the complementary binary amplitude mask over the first hologram. The operation principle of our system is explained with the well-known theory of recording and reading a volume hologram in a photorefractive material and the experimental results are presented. Experimental data show that our encryption system is protected from blind decryptions by randomly-generated incorrect amplitude masks.

• Journal of Korea Multimedia Society
• /
• v.12 no.2
• /
• pp.209-218
• /
• 2009

3D backprojection is a kind of reconstruction algorithm to generate volume data consisting of tomographic images, which provides spatial information of the original 3D data from hundreds of 2D projections. The computational time of backprojection increases in proportion to the size of volume data and the number of projection images since the value of every voxel in volume data is calculated by considering corresponding pixels from hundreds of projections. For the reduction of computational time, fast GPU based 3D backprojection methods have been studied recently and the performance of them has been improved significantly. This paper presents two multiple GPU based methods to maximize the parallelism of GPU and compares the efficiencies of two methods by considering both the number of projections and the size of volume data. The first method is to generate partial volume data independently for all projections after allocating a half size of volume data on each GPU. The second method is to acquire the entire volume data by merging the incomplete volume data of each GPU on CPU. The in-complete volume data is generated using the half size of projections after allocating the full size of volume data on each GPU. In experimental results, the first method performed better than the second method when the entire volume data can be allocated on GPU. Otherwise, the second method was efficient than the first one.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.35 no.4
• /
• pp.261-268
• /
• 2017

The topographic volume estimation is carried out for the earth work of a construction site and quarry excavation monitoring. The topographic surveying using instruments such as engineering levels, total stations, and GNSS (Global Navigation Satellite Systems) receivers have traditionally been used and the photogrammetric approach using drone systems has recently been introduced. However, these methods cannot be adopted for inaccessible areas where high resolution satellite images can be an alternative. We carried out experiments using Kompsat-3/3A data to estimate topographic volume for a quarry and checked the accuracy. We generated DEMs (Digital Elevation Model) using newly acquired Kompsat-3/3A data and checked the accuracy of the topographic volume estimation by comparing them to a reference DEM generated by timely operating a drone system. The experimental results showed that geometric differences between stereo images significantly lower the quality of the volume estimation. The tested Kompsat-3 data showed one meter level of elevation accuracy with the volume estimation error less than 1% while the tested Kompsat-3A data showed lower results because of the large geometric difference.

• Journal of Korea Game Society
• /
• v.9 no.6
• /
• pp.191-196
• /
• 2009

Volume rendering is a method which extracts meaningful information from volume data and visualizes those information. In general, since the size of volume data gets larger, it is very important to devise acceleration methods for interactive rendering speed. Min-max octree is data structure for high-speed volume rendering, however, its creation time becomes long as the data size increases. In this paper, we propose acceleration method of min-max octree generation using CUDA. Firstly, we convert one-dimensional array from volume data using space filling curve. Then we make min-max octree structures from the sequential array and apply them to acceleration of volume ray casting.