Procedural Texture Research Articles

Gentropy: evolving 2D textures

Gentropy is a genetic programming system that evolves two-dimensional procedural textures. It synthesizes textures by combining mathematical and image manipulation functions into formulas. A formula can be reevaluated with arbitrary texture-space coordinates, to generate a new portion of the texture in texture space. Most evolutionary art programs are interactive, and require the user to repeatedly choose the best images from a displayed generation. Gentropy uses an unsupervised approach, where one or more target texture image is supplied to the system, and represent the desired texture features, such as colour, shape and smoothness (contrast). Then, Gentropy evolves textures independent of any further user involvement. The evolved texture will not be identical to the target texture, but rather, will exhibit characteristics similar to it. When more than one texture is supplied as a target, multi-objective feature analysis is performed. These feature tests may be combined and given different priorities during evaluation. It is therefore possible to use several target images, each with its own fitness function measuring particular visual characteristics. Gentropy also permits the use of multiple subpopulations, each of which may use its own texture evaluation criteria and target texture.

Estimating Parameters for Procedural Texturing by Genetic Algorithms

Procedural texturing has been an active research area in computer graphics with some open problems still unsolved (D. S. Ebert, F. K. Musgrave, K. P. Peachey, K. Perlin, and S. Worley, 1998, Texturing and Modeling: A Procedural Approach, Academic Press, San Diego). One major problem is on how to estimate or recover the parameter values for a given procedural texture using the input texture image if the original parameter values are not available. In this paper, we propose a solution to this problem and present a genetic-based multiresolution parameter estimation approach. The key idea of our approach is to use an efficient search method (a genetic-based search algorithm is used in this paper) to find appropriate values of the parameters for the given procedure. During the search process, for each set of parameter values, we generate a temporary texture image using the given texturing procedure; then we compare the temporary texture image with the given target texture image to check if they match. The comparison between two texture images is done by using a multiresolution MRF texture model. The search process stops when a match is found. The estimated values of the parameters for a given procedure are the values of the parameters to the procedure to generate a texture image that matches the target texture image. Experimental results are presented to demonstrate the success of our approach. Application of our parameter estimation approach to texture synthesis is also discussed in the paper.

The Texture Animator

This paper discusses three distinct techniques for the animation of procedural textures and describes a software tool. Animation is attained by moving the rendered point before the texture evaluation, changing the definition of the texture space or changing the texture colour mapping. Examples are given for textures based on noise and turbulence functions in order to simulate natural phenomena. Some phases of the texture animation process can be automated using a code generator supported by a library of animation effects. Aspects of practical implementation are discussed and Renderman compliant code is presented.

Preserving attribute values on simplified meshes by resampling detail textures

Many sophisticated solutions have been proposed to reduce the geometric complexity of 3D meshes. A less studied problem is how to preserve on a simplified mesh the detail (e.g. color, high frequency shape detail, scalar fields, etc.) which is encoded in the original mesh. We present a general approach for preserving detail on simpli-fied meshes which is completely independent on the simplification technique adopted to reduce mesh size. The detail (or high frequency information) lost after simplification is encoded through texture or bump maps. The original contribution is that preservation is performed after simplification, by building set of triangular texture patches that are then packed in a single texture map. Each simplified mesh face is sampled to build the associ-ated triangular texture patch; different methods for storing this set of texture patches into a standard rectangular texture are presented and discussed. The solution is very general, because it can be applied to the output of any simplification code and because it allows preservation of any attribute value defined on the high resolution mesh. Moreover, the produced mesh de-couples shape from detail (the latter is encoded with texture maps) and allows highly efficient rendering. We also describe an alternative application: the conversion of 3D models with 3D procedural textures (which generally force the use of a software renderers) into standard 3D models with 2D bitmap textures, which con-versely can be rendered on any standard HW/SWgraphics subsystem. EMAIL:: r.scopigno@cnuce.cnr.it

Comprehensive Halftoning of 3D Scenes

The display of images on binary output hardware requires a halftoning step. Conventional halftoning algorithms approximate image values independently from the image content and often introduce artificial texture that obscures fine details. The objective of this research is to adapt a halftoning technique to 3D scene information and thus to enhance the display of computer generated 3D scenes. Our approach is based on the control of halftoning texture by the combination of ordered dithering and error diffusion techniques. We extend our previous work and enable a user to specify the shape, scale, direction, and contrast of the halftoning texture using an external buffer. We control texture shape by constructing a dither matrix from an arbitrary image or a procedural texture. Texture direction and scale are adapted to the external information by the mapping function. Texture contrast and the accuracy of tone reproduction are varied across the image using the error diffusion process. We halftone images of 3D scenes by using the geometry, position, and illumination information to control the halftoning texture. Thus, the texture provides visual cues and can be used to enhance the viewer's comprehension of the display.

Simulating Wood Using a Voxel Approach

In this paper we present a technique for generating three‐dimensional wood textures using a regular texture array. Currently three‐dimensional wood textures are generated using procedural textures. Procedural textures are flexible and require little memory, however the modeling of local artifacts such as knots is difficult using the procedural approach. By representing the wood as a texture array and growing the wood in this array we can easily simulate local phenomena such as knots. Our growth model is an approximation to the biological model and assumes that there are several similar wood cells per array element. This means that we can model artifacts that are defined by groups of similar cells. In particular our model is well suited for the modeling of soft‐woods.

Fractal pattern for a butterfly wing

The texture pattern of abutterfly wing is very complicated but beautiful. We propose a new and effective procedural texture generation approach using the traits of iteration behavior to synthesize the texture patterns of a butterfly wing realistically. Based on the traits of the iteration process, the graphical behaviors near and between attractive fixed points can model the pattern ofeyelike spots andriverlike bands, respectively. Some realistic wing patterns are presented to show the effectiveness of this method.

Texture mapping for scientific visualization environments

This study presents the use of texture functionalities in order to increase the possibilities of data sets' visualization. We start from a specific iconic representation of a vectorial field in which, e.g., a cone-shaped solid icon represents a vector in the 3D space. We then produce undulations on the surface of the icon and a perturbation of its colour by means of texture techniques. We observed that mapping undulations and colour perturbation to other variables of the phenomenon describing scalar fields, increases the amount of icon-conveyed information. Then we report some remarks about the implementation of a procedural texture function and the texture capabilities are demonstrated examining an application example where the implemented function has been used in a scientific visualization environment.

Graphics goodies #2—a simple, versatile procedural texture

Graphics goodies #2—a simple, versatile procedural texture