Oubong Gwun

Binary synchronization of chaos in hybrid cellular automata for low complexity image compression and transmission

This paper exploits an interesting property of a certain type of elementary cellular automata, namely hybrid cellular automata (HCA) defined by rule 101 and its negate. Such HCA may be easily implemented on any CNN platform, and has some interesting properties. It provides a chaotic counting automaton instead of the traditional raster scan counter addressing the multiple sensing elements. Replacing raster scan with chaotic scan provided by the HCA allows implementation of both progressive image compression and spread spectrum transmission with a very low complexity of the transmitting sensor. The clear advantages of our system in terms of implementation complexity, makes it a valuable candidate for low power sensor networks applications.

Three-dimensional image modeling based on least squares fitting by using adaptive subdivision of a tetrahedron

3D image modeling system is highly demanded for automated visual inspection and non-destructive testing. It also can be useful to biomedical research, medical therapy, surgery planning, and simulation of critical surgery. Image processing and image analysis are used to enhance and classify the medical volumetric data. Analyzing medical volumetric data is very difficult. In this paper, we propose a new image modeling method based on least squares fitting by adaptive sub-division of tetrahedron. First, each pixel of the given medical image is enhanced through image processing. next, initial tetrahedral domain is constructed based on sphere criterion with the selected pixels. Finally, refining process is performed through sub-division of tetrahedron based on least squares fitting. User can specify the tolerance. Sub-division is continued until difference between approximation and measured value is less than specified tolerance.

Automatic Estimation of Live Coffee Leaf Infection based on Image Processing Techniques

Image segmentation is the most challenging issue in computer vision applications. And most difficulties for crops management in agriculture are the lack of appropriate methods for detecting the leaf damage for pests’ treatment. In this paper we proposed an automatic method for leaf damage detection and severity estimation of coffee leaf by avoiding defoliation. After enhancing the contrast of the original image using LUT based gamma correction, the image is processed to remove the background, and the output leaf is clustered using Fuzzy c-means segmentation in V channel of YUV color space to maximize all leaf damage detection, and finally, the severity of leaf is estimated in terms of ratio for leaf pixel distribution between the normal and the detected leaf damage. The results in each proposed method was compared to the current researches and the accuracy is obvious either in the background removal or damage detection.

An Integrated Simulation Environment Which Automatically Generates and Edits Source Code for Geant4: Geant4Editor

Geant4 is a physical library, used for radiation or other physics simulations. To take advantage of the Geant4 library, the user should inherit the classes which are provided in the library and embody the three classes required by C++ language. Because it is usually difficult and takes a lot of time for a physicist to embody these classes, we are developing a user interface system named Geant4Editor in order to provide a more convenient integrated simulation environment in which to edit and generate the Geant4 source code. In this paper, we explore the weak points of the existing programs, and analyze the Geant4 library execution process and mandatory class definition rules, so as to allow the mandatory classes to be generated simply by inputting parameters and to provide a more convenient integrated simulation environment. Geant4Editor is based on Win32, and runs in the Windows environment.

3D image modeling based on tetrahedral domain by using wavelet transformation

3D image modeling of volumetric data is highly demanded for automated visual inspection and non-destructive testing. It also can be useful to biomedical research, medical therapy, surgery planning, and simulation of critical surgery. The common problem of volumetric image data is that the amount of data is too much. This paper proposes a method which selects the important data by using wavelet transformation, and refines the constructed tetrahedral domain until the difference between the approximation and the measured value is less than the specified tolerance. The resulting interpolant can be visualized by using iso-surface rendering. We call this new algorithm as marching tetrahedra for the purpose of comparing to marching cubes algorithm. The main difference between two algorithms is tetrahedra are used instead of cubes. Therefore, we can avoid the ambiguity problem of marching cubes algorithm.

3D medical data visualization using SVG

Recently the Web gives us a universal interface and platform independent functionality. An important part of web browser is providing a format for representing 3D medical data. In this paper we classified 3D medical information into 3 types; 3D medical volume data, 3D medical image, volume rendering application. And then we represented each of them with XML. It enables us to understand the 3D medical data much more. In addition we represented direct volume rendering application based on text map with SVG and viewed the results on the SVG viewer. The results showed that it is possible to script volume rendering application with SVG and to look at the 3D medical image on the SVG viewer.

A boundary surface based ray casting using 6-depth buffers

This paper focuses on boundary surface based ray casting. In general the boundary surface based ray casting is processed in two stages. In the first stage, boundary surfaces are found and stored into buffers. In the second stage, the distance between the viewpoint and the voxels of the area of interest is calculated by projecting boundary surfaces on the view plane, and then the traverse of the volume data space with the distance is started. Our approach differs from the general boundary surface ray casting in its first stage. In contrast to the typical boundary surface based ray casting where all boundary surfaces of volume data are stored into buffers, in our proposal, they are projected on the planes aligned to the axis of volume data coordinates and these projected data are stored into 6-depth buffers. Such a maneuver shortens the time for ray casting, and reduces memory usage because it can be carried out independently from the amount of the volume data.

A three-dimensional model of primary thrombus formation based on fluid dynamics and level sets

ABSTRACT In this paper, a three-dimensional (3D) multiscale model is proposed for the formation process of a primary thrombus. In the model, blood plasma is modelled by Navier–Stokes equations in macroscale because the blood plasma is seen as a continuous viscous fluid. The adhesion and aggregation of platelets are the main physiological processes of primary thrombus formation. As platelets and the primary thrombus are seen as rigid solids, these physiological processes are modelled in microscale according to the force related to the distance between the two solid bodies. We use level sets to represent the growth of the primary thrombus in 3D, and the multiscale model is applied to the 3D simulation of the primary thrombus formation. From numerical observations, the appearance of the formation process shows that it was affected by the change of blood-flow velocities. We can conclude that the appearance of the primary thrombus affects vascular blood flow.

Leaf Modeling and Growth Process Simulation Using the Level Set Method

This paper presents a simulation of the growth process of leaves for computer graphics, visualization, and virtual reality applications. The following two-stage simulation is presented in this paper. First, a reference image is used to guide the early stage growth of the leaf; second, a growth function was created based on several vector fields controlled by a generalized logistic function. This growth function allows the leaf growth to continue beyond the information provided by the reference image. The core of both stages is the use of the level set method to extract and evolve the leaf shape. The proposed method facilitates the creation of frequently needed objects in an easy and flexible way that releases the user, usually an animator, from the burden of animating a leaf, which is usually a background object in a scene. We present several results from our experiments using various growth parameters and different leaves to showcase the advantages of using our method.

3D simulation of primary thrombus formation based on Level Set Methods

The simulation of thrombosis is a popular research topic recently. Since Level Set Methods have well developed in fluid flow simulation, this paper presents a 3D simulation of primary thrombus formation based on Level Set Methods. A hybrid model including a macroscale model and a microscale model is built to simulate the flow, adhesion, and aggregation of platelets. The macroscale model is based on Navier-Stokes equations and the microscale model is described as external force and viscosity increase of platelets. By this simulation we observe the process of primary thrombus formation and analyze the effect of Reynolds Number (Re) to the formation rate. The results show that the formation rate increases with Re rise and this phenomenon becomes significant when Re is larger than the normal average Re of vessels which is a threshold value.