Cellular Automata for Imaging, Art, and Video

2003 ◽  
Author(s):  
Joy V. Hughes
Keyword(s):  
Cellular Automata ◽  
State Space ◽  
Color Space ◽  
Three Dimensional ◽  
Difficult Problem ◽  
Special Effects ◽  
Color Wheel ◽  
Distorted Version ◽  
Artistic Medium ◽  
A Cell

The techniques known as Cellular Automata (CA) can be used to create a variety of visual effects. As the state space for each cell, 24-bit photo realistic color was used. Several new state transition rules were created to produce unusual and beautiful results, which can be used in an interactive program or for special effects for images or videos. This chapter presents a technique for applying CA rules to an image at several different levels of resolution and recombining the results. A “soft” artistic look can result. The concept of “targeted” CAs is introduced. A targeted CA changes the value of a cell only if it approaches a desired value using some distance metric. This technique is used to transform one image into another, to transform an image to a distorted version of itself, and to generate fractals. The author believes that the techniques presented can form the basis for a new artistic medium that is partially directed by the artist and partially emergent. Images and animations from this work are posted on the World Wide Web at (http://www.scruznet.com/~hughes/CA.html). All cellular automata (CA) operate on a space of discrete states. The simplest CAs, such as the Game of Life, use a 1-bit state space. Most modern personal computers represent color as a 24-bit value, allowing for approximately 16 million possible colors. The work presented in this chapter uses a 24-bit color space that is represented in a 32-bit-long integer. This color space can be conceptualized as a three-dimensional bounded continuous vector space. Often, it is desirable to work with in the HSV (Hue, Saturation, Value) color space. Some of the rules encode the value (luminance) of a cell in the otherwise unused 8 high-order bits of a 32-bit word. The hue and saturation can be estimated “on the fly” with simple, fast algorithms. The hue is represented as an angle on the color wheel. For some rules, it is necessary to know the “distance” between two colors. Estimating the distance in perceptual space would be a difficult problem, as it would be dependent on the monitor used and the gamma exponent applied for a particular setup.

scholarly journals Leukocyte recognition with convolutional neural network

2018 ◽  
Vol 13 ◽  
pp. 174830181881332 ◽  
Author(s):  
Liqun Lin ◽  
Weixing Wang ◽  
Bolin Chen
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
White Blood Cells ◽  
Color Space ◽  
Difficult Problem ◽  
Segmentation Accuracy ◽  
Feature Weight ◽  
A Cell ◽  
Clustering Center ◽  
Blood Smear Image

Accurate segmentation of leukocytes is a primary and very difficult problem because of the non-uniform color, uneven illumination of blood smear image. An improved algorithm based on feature weight adaptive K-means clustering for extracting complex leukocytes is proposed. In this paper, the initial clustering center is chosen according to the histogram distribution of a cell image; this approach not only improves the clustering effect but also reduces the time complexity of the algorithm from O (n) to O (1). Prior to white blood cell extraction, the color space is decomposed. Then, color space decomposition and K-means clustering are combined for image segmentation. And then adherent complex white blood cells are separated again based on watershed algorithm. Finally, classification experiments based on convolutional neural network were performed and compared with other methods; 368 representative images were used to evaluate the performance of our method. The proposed segmentation method achieves 95.81% segmentation accuracy. The classification accuracy reached a maximum of 98.96%, and the average classification time is 0.39 s. Compared with those in the existing algorithms for WBC, convolutional neural network classification method not only presents obvious advantages but can also be easily improved.

Simulating Self-Regeneration and Self-Replication Processes Using Movable Cellular Automata with a Mutual Equilibrium Neighborhood

2020 ◽  
Vol 29 (4) ◽  
pp. 741-757
Author(s):  
Kateryna Hazdiuk ◽  
◽  
Volodymyr Zhikharevich ◽  
Serhiy Ostapov ◽  
◽  
...  
Keyword(s):  
Cellular Automata ◽  
Cellular Automaton ◽  
Three Dimensional ◽  
Computer Models ◽  
The Self ◽  
Model Construction ◽  
Natural Phenomena ◽  
Different Types ◽  
Movable Cellular Automata ◽  
Self Replication

This paper deals with the issue of model construction of the self-regeneration and self-replication processes using movable cellular automata (MCAs). The rules of cellular automaton (CA) interactions are found according to the concept of equilibrium neighborhood. The method is implemented by establishing these rules between different types of cellular automata (CAs). Several models for two- and three-dimensional cases are described, which depict both stable and unstable structures. As a result, computer models imitating such natural phenomena as self-replication and self-regeneration are obtained and graphically presented.

A Three-Dimensional Viscous Transonic Inverse Design Method

2000 ◽  
Author(s):  
W. T. Tiow ◽  
M. Zangeneh
Keyword(s):  
Design Method ◽  
Flow Analysis ◽  
Three Dimensional ◽  
Viscous Effects ◽  
Flow Equations ◽  
Flow Solution ◽  
Turbomachinery Blades ◽  
A Cell ◽  
Inverse Design Method ◽  
Euler Solver

The development and application of a three-dimensional inverse methodology is presented for the design of turbomachinery blades. The method is based on the mass-averaged swirl, rV~θ distribution and computes the necessary blade changes directly from the discrepancies between the target and initial distributions. The flow solution and blade modification converge simultaneously giving the final blade geometry and the corresponding steady state flow solution. The flow analysis is performed using a cell-vertex finite volume time-marching algorithm employing the multistage Runge-Kutta integrator in conjunction with accelerating techniques (local time stepping and grid sequencing). To account for viscous effects, dissipative forces are included in the Euler solver using the log-law and mixing length models. The design method can be used with any existing solver solving the same flow equations without any modifications to the blade surface wall boundary condition. Validation of the method has been carried out using a transonic annular turbine nozzle and NASA rotor 67. Finally, the method is demonstrated on the re-design of the blades.

USE OF ONLINE TECHNOLOGIES TO BUILD THREE-DIMENSIONAL CELLULAR AUTOMATA

2021 ◽  
Vol 22 ◽  
pp. 39-47
Author(s):  
O Zelevska ◽  
◽  
O Finogenov ◽  
I Ibnukhsein ◽  
V Suvorova ◽  
...  
Keyword(s):  
Cellular Automata ◽  
Three Dimensional ◽  
Online Technologies

The Development of an Automatic Three-Dimensional Mesh Generator via Modified Ray Casting

1992 ◽  
Author(s):  
Cengiz Yeker ◽  
Ibrahim Zeid
Keyword(s):  
Finite Elements ◽  
Cell Structure ◽  
Three Dimensional ◽  
Ray Casting ◽  
Solid Object ◽  
Casting Technique ◽  
Element Size ◽  
A Cell ◽  
Conforming Meshes ◽  
Representation Scheme

Abstract A fully automatic three-dimensional mesh generation method is developed by modifying the well-known ray casting technique. The method is capable of meshing objects modeled using the CSG representation scheme. The input to the method consists of solid geometry information, and mesh attributes such as element size. The method starts by casting rays in 3D space to classify the empty and full parts of the solid. This information is then used to create a cell structure that closely models the solid object. The next step is to further process the cell structure to make it more succinct, so that the cells close to the boundary of the solid object can model the topology with enough fidelity. Moreover, neighborhood relations between cells in the structure are developed and implemented. These relations help produce better conforming meshes. Each cell in the cell structure is identified with respect to a set of pre-defined types of cells. After the identification process, a normalization process is developed and applied to the cell structure in order to ensure that the finite elements generated from each cell conform to each other and to other elements produced from neighboring cells. The last step is to mesh each cell in the structure with valid finite elements.

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