%0 Journal Article %1 wiens:2002:cg %A Wiens, Andrea L. %A Ross, Brian J. %D 2002 %J Computers and Graphics %K Evolution, Procedural algorithms, genetic graphics programming, textures, %N 1 %P 75--88 %T Gentropy: Evolutionary 2D Texture Generation %U http://citeseer.ist.psu.edu/503669.html %V 26 %X 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 re-evaluated 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 are 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, multiobjective 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.

@article{wiens:2002:cg, abstract = {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 re-evaluated 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 are 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, multiobjective 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.}, added-at = {2008-06-19T17:35:00.000+0200}, author = {Wiens, Andrea L. and Ross, Brian J.}, biburl = {https://www.bibsonomy.org/bibtex/2d3fac17a8ba18eec2911011550bcbaba/brazovayeye}, interhash = {b04b43d4c02105eb13845dddcb00804b}, intrahash = {d3fac17a8ba18eec2911011550bcbaba}, journal = {Computers and Graphics}, keywords = {Evolution, Procedural algorithms, genetic graphics programming, textures,}, month = {February}, notes = {http://www.cosc.brocku.ca/~bross/gentropy/}, number = 1, pages = {75--88}, timestamp = {2008-06-19T17:54:11.000+0200}, title = {Gentropy: Evolutionary 2{D} Texture Generation}, url = {http://citeseer.ist.psu.edu/503669.html}, volume = 26, year = 2002 }