基于遗传算法的分形艺术图案生成方法的研究
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摘要
当今社会,随着人们生活水平的提高,生活节奏的加快,人们的消费观念也逐渐发生着变化。在购买商品时,消费者不仅关注商品的实用性,而且越来越重视商品的外观与造型的艺术性。商品的艺术性在无形中提高了商品的品味,也同时提高了该商品在人们心目中的价值。
艺术设计工作中很大一部分工作是艺术图案设计。分形是描述不规则几何形态的有力工具,分形几何图案表现的特点是整体上的处处不规则性和不同尺度上图形的规则性。利用分形的自相似性和自生长性,可以构造出千变万化而又具有高分辨率结构的艺术图案。因此,分形理论十分适用于艺术图案的辅助设计。
遗传算法(Genetic Algorithm,GA)是由美国的霍兰德(J.Holland)于1975年提出的,是一种借鉴生物界自然选择和自然遗传机理的随机化搜索算法。近30多年来,由于遗传算法求解复杂优化问题的巨大潜力及其在各个领域应用的成功,这种算法受到了广泛的关注和研究。
本文致力于对基于遗传算法的分形艺术图案生成方法的研究,目的是通过探索分形理论与遗传算法相结合的分形艺术图案的生成方法,为艺术图案创新设计者提供高效、方便的支持环境,为更快、更好地满足用户提出的设计需求提供有利帮助。
主要工作为:
1、将分形理论及遗传算法相结合,在基于复动力系统生成方法与文法构图生成方法的基础上,提出了基于遗传算法的广义M-J集生成方法与LS文法构图生成方法。
2、在遗传算法中,通过加入人机交互,将用户偏好融入到遗传过程,以反映设计人员的设计思想。同时,解决了概念设计中适应度函数难以表达的问题。采用自适应方法,保证了遗传群体的优良性。
3、将上述方法应用于基于遗传算法的分形图案绘图系统中,验证了上述方法的有效性。
Nowadays,with the improvement of the standard of living and the pace of life becoming faster and faster, people’s sense of consume is changing gradually.The practicality of merchandises is concerned by consumers when they buy somehthing.Meanwhile, They pay more and more attention to the artistic quality of the merchandise’s appearance and sculpt. The artistic quality of merchandises not only improve the taste of merchandises virtually,but also improve the value of merchandises in people’s mind.
The most part of the work in the artistic design is artistic graphics design. Fractal is an effect tool to describe irregular geometrical shapes,characteristic of fractal graphics is the irregular trait as a whole and the regular trait in part.The daedal fractal artistic graphics with high resolution are constructed,for the fractal graphs have the self-similar and self-growing characteristic . Therefore, fractal theory is very suitable to the CAD of the artistic graphics.
Genetic Algorithm , put forward by J.Holland in the USA in 1975 , is a randomly searching algorithm,which use natural selection and natural genetic mechanism as reference.Genetic Algorithm has obtained favor from many scholars and engineers for its potential to solve complex optimizing problems and the successful application in various fields during the past 30 years.
This paper applies itself to research the generation methods of the fractal artistic graphics based on Genetic Algorithm. Its purpose is to provide high-efficient and convenient support environment for the artistic graphics designers and a better help to meet the demands of design by exploring the generation method of the fractal artistic graphics combining fractal theory and Genetic Algorithm.
the main job is:
1.To combining Genetic Algorithm and fractal theory,on the foundation of the generation method based on complex dynamic system and grammatical composition ,put forward the new generation methods of generalized Mandelbrot- Julia sets and LS grammatical composition based on Genetic Algorithm.
2. Users’profile is melted into the genetic process which reflect the design idea of designers by adding human-computer interaction in Genetic Algorithm. Meanwhile, the problem of fitness function expression is solved in conceptual design. The good population is protected by adopting the adaptive method
3. The above methods are applied to the fractal graphics drawing system based on Genetic Algorithm to proved their validity.
艺术设计工作中很大一部分工作是艺术图案设计。分形是描述不规则几何形态的有力工具,分形几何图案表现的特点是整体上的处处不规则性和不同尺度上图形的规则性。利用分形的自相似性和自生长性,可以构造出千变万化而又具有高分辨率结构的艺术图案。因此,分形理论十分适用于艺术图案的辅助设计。
遗传算法(Genetic Algorithm,GA)是由美国的霍兰德(J.Holland)于1975年提出的,是一种借鉴生物界自然选择和自然遗传机理的随机化搜索算法。近30多年来,由于遗传算法求解复杂优化问题的巨大潜力及其在各个领域应用的成功,这种算法受到了广泛的关注和研究。
本文致力于对基于遗传算法的分形艺术图案生成方法的研究,目的是通过探索分形理论与遗传算法相结合的分形艺术图案的生成方法,为艺术图案创新设计者提供高效、方便的支持环境,为更快、更好地满足用户提出的设计需求提供有利帮助。
主要工作为:
1、将分形理论及遗传算法相结合,在基于复动力系统生成方法与文法构图生成方法的基础上,提出了基于遗传算法的广义M-J集生成方法与LS文法构图生成方法。
2、在遗传算法中,通过加入人机交互,将用户偏好融入到遗传过程,以反映设计人员的设计思想。同时,解决了概念设计中适应度函数难以表达的问题。采用自适应方法,保证了遗传群体的优良性。
3、将上述方法应用于基于遗传算法的分形图案绘图系统中,验证了上述方法的有效性。
Nowadays,with the improvement of the standard of living and the pace of life becoming faster and faster, people’s sense of consume is changing gradually.The practicality of merchandises is concerned by consumers when they buy somehthing.Meanwhile, They pay more and more attention to the artistic quality of the merchandise’s appearance and sculpt. The artistic quality of merchandises not only improve the taste of merchandises virtually,but also improve the value of merchandises in people’s mind.
The most part of the work in the artistic design is artistic graphics design. Fractal is an effect tool to describe irregular geometrical shapes,characteristic of fractal graphics is the irregular trait as a whole and the regular trait in part.The daedal fractal artistic graphics with high resolution are constructed,for the fractal graphs have the self-similar and self-growing characteristic . Therefore, fractal theory is very suitable to the CAD of the artistic graphics.
Genetic Algorithm , put forward by J.Holland in the USA in 1975 , is a randomly searching algorithm,which use natural selection and natural genetic mechanism as reference.Genetic Algorithm has obtained favor from many scholars and engineers for its potential to solve complex optimizing problems and the successful application in various fields during the past 30 years.
This paper applies itself to research the generation methods of the fractal artistic graphics based on Genetic Algorithm. Its purpose is to provide high-efficient and convenient support environment for the artistic graphics designers and a better help to meet the demands of design by exploring the generation method of the fractal artistic graphics combining fractal theory and Genetic Algorithm.
the main job is:
1.To combining Genetic Algorithm and fractal theory,on the foundation of the generation method based on complex dynamic system and grammatical composition ,put forward the new generation methods of generalized Mandelbrot- Julia sets and LS grammatical composition based on Genetic Algorithm.
2. Users’profile is melted into the genetic process which reflect the design idea of designers by adding human-computer interaction in Genetic Algorithm. Meanwhile, the problem of fitness function expression is solved in conceptual design. The good population is protected by adopting the adaptive method
3. The above methods are applied to the fractal graphics drawing system based on Genetic Algorithm to proved their validity.
引文
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[30]宋广为,徐晨.分形在激光全息防伪系统中的应用研究[J].信息与控制.2005,34(5):557-566
[31]郭冬梅,孙兰凤,谷永茂.计算机分形图形技术的研究[J].计算机应用.2000,20:47-48
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[36]王兴元,刘威.利用陷阱技术构造伪3D牛顿变换的M-J集[J].计算机辅助设计与图形学学报.2005,17(4):754-760
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[39]李庆忠,韩金姝.基于IFS的树木形态模拟真实感的研究.微机发展.2005,15(7):255-258
[40]田金超,孟克,韩志学,一种基于迭代函数系统的分形图像编码方法,应用科技,2005,32(7):256-263。
[41]冯玲.遗传算法在分形图案自动化设计中的应用[J].计算机工程与设计.2008, 29(12): 3185-3187
[42]李敏强.遗传算法的基本理论与应用[M].科学出版社.2002
[43]张奇,陈国初,俞金寿.基于人工生命的优化方法及应用[J].华东理工大学学报(自然科学版).2008,24(2):273-277
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[47]叶瑞松.复动力系统生成的拟3D分形图像[J].计算机辅助设计与图形学学报. 2001,13 (10):865-867
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[2]韩向峰基于分形理论的创新设计及其应用[D].硕士论文.2005
[3]杨旭洪,李栋高,颜晓花.给予分形L系统的纺织品图案的自动生成[J].纺织学报.2003,24(3):193-195
[4]曾文曲,王向阳.分形理论与分形的计算机模拟[M].沈阳:东北大学出版社,1993.
[5]齐东旭.分形及其计算机生成[M].北京:科学出版社,1996
[6] Michalewicz Z. Genetic Algorithms + Data Structures = Evolution Programs[M]. Springer- Verlag, Second, Extended Edition, 1994
[7]李敏强.遗传算法的基本理论与应用[M].科学出版社.2002
[8]陈国良,王煦法,等.遗传算法及其应用[M].北京:民邮电出版社,1996.
[9] BENTLEY P J, CORNE D W. Introduction to creative evolutionary systems [M].San Francisco: Morgan Kaufmann Publishers Inc,2001.
[10]Grefenstette J J. GENESIS: A System for Using Genetic Search Procedures[C].In: Proceedings of the 1984 Conference on Intelligent Systems and Machines, 1984:161-165
[11]Liu X.Y., Frazer J.H., Tang M.X., A generative design system based on evolutionary and mathematical functions[C], Generative Art 2002, Milan, Italy, 2002
[12]武晓今,朱仲英.遗传算法多样性测度问题研究[J].信息与控制,2005,34(4):416-427.
[13]王允建,江锋锁,李钟侠.混沌遗传算法在函数优化中的应用[J].测控技术,2005,24 (2):65-66.
[14]Masanori Sugisaka,Xinjian Fan.Adaptive Genetic Algorithm with a Cooperative Mode[C].In:Proceedings of IEEE International Symposium on Industrial Electronics,2001
[15]D E Goldberg.Genetic Algorithm in Search,Optimization,and Machine Learning [M].Addison-Wesley,1989
[16]B.B.Mandelbrot,Fratcals:Form,Chance and Dimension,San Francisco,Freeman , 1977
[17]Mandelbrot,B.B.The Fractal Geometry of Nature.Freeman,San Francisco.1982.
[18]Falconer K J.分形几何—数学基础及其应用[M]。沈阳:东北大学出版社,1991
[19]孙博文.分形算法与程序设计Visual Basic实现[M].北京科学出版社.2004
[20] ZHAO YuXin,YI ShiHe, TIAN LiFeng, HE Lin ,CHENG ZhongYu.The fractal measurement of experimental images of supersonic turbulent mixing layer[J]. Sci China Ser G-Phys Mech Astron.2008,51 (8):1134-1143
[21]秦耀辰,刘凯.分形理论在地理学中的应用研究进展[J].地理科学进展.2003, 22(4): 426 -436
[22]张捷,包浩生.分形理论及其在地貌学中的应用.地理研究,1994,13(3):104- 112.
[23]岳文泽,徐建华等.分形理论在人文地理学中的应用研究.地理学与国土研究.2001,17 (2):51-56.
[24]肖杨,梁千,王丽君.资本市场中分形市场分析的理论探讨[J].金融经济.2008,16:85-86
[25]张雪花,郭怀成,张宏伟.区域经济联系强度的分形特征分析及其在我国西部地区的应用[J].北京大学学报(自然科学版).2007, 43 (2):245-250
[26]张小民,吴群琪.公路规模-经济产出的分形理论模型[J].中国公路学报.2008,21(1): 106-110
[27]张森文,张强.分形理论在农业与食品系统中的应用综述[J].农业工程学报.2002,18 (5):13-18
[28]Slawomir S. Nikiel. True-colour images and iterated function systems [J]. Computer & Graphics, 1998,22(5): 635-640.
[29] D. J. Duh,J. H. Jeng,S. Y. Chen. Speed quality control for fractal image compression[J]. The Imaging Science Journal.2008,56(2):79-90
[30]宋广为,徐晨.分形在激光全息防伪系统中的应用研究[J].信息与控制.2005,34(5):557-566
[31]郭冬梅,孙兰凤,谷永茂.计算机分形图形技术的研究[J].计算机应用.2000,20:47-48
[32]李水根,分形,高等教育出版社[M],2004
[33]胡纪阳,胡瑞安.Mandelbrot集及非线性过程的可视化[J]:计算机辅助设计及图形学学报.1991,3(4):26-32
[34]秦宣云,管继虹,任波,韩旭里.广义Julia集关于迭代参数的对称性分析[J].计算机辅助设计及图形学学报.2007.19(7):927-930
[35]王兴元.广义M-J集的分形机理[M].大连:大连理工大学出版社, 2002
[36]王兴元,刘威.利用陷阱技术构造伪3D牛顿变换的M-J集[J].计算机辅助设计与图形学学报.2005,17(4):754-760
[37]Mandelbrot.The Fractal Geometry of Nature.Free-man.NewYork,1982,21:25-34
[38]Prusinkiewic Z,Lindenmayer P.Developmental models of herbaceous plants for computer imagery purpose.ACM SIIGGRAPH,1988,22(4):223-228
[39]李庆忠,韩金姝.基于IFS的树木形态模拟真实感的研究.微机发展.2005,15(7):255-258
[40]田金超,孟克,韩志学,一种基于迭代函数系统的分形图像编码方法,应用科技,2005,32(7):256-263。
[41]冯玲.遗传算法在分形图案自动化设计中的应用[J].计算机工程与设计.2008, 29(12): 3185-3187
[42]李敏强.遗传算法的基本理论与应用[M].科学出版社.2002
[43]张奇,陈国初,俞金寿.基于人工生命的优化方法及应用[J].华东理工大学学报(自然科学版).2008,24(2):273-277
[44] BENTLEY P J, CORNE D W. Introduction to creative evolutionary systems [M].San Francisco: Morgan Kaufmann Publishers Inc,2001.
[45]D E Goldberg.Genetic Algorithm in Search,Optimization,and Machine Learning [M]. Addison-Wesley , 1989
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