Interactive Product Color Design Integrating Users' Cognitive Noise using Interactive Genetic Algorithms
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摘要: 产品配色设计对塑造产品风格和企业品牌形象有重要作用，为有效辅助工业设计师进行产品配色设计，准确反映用户对产品配色方案的意象感知，利用交互式遗传算法集成用户认知度和疲劳度构建了认知噪声模型，根据产品配色方案评价值和色彩值的相似度测量求解认知噪声模型相关参数，对配色方案适应度值进行调整，提出了考虑用户认知噪声的产品交互式配色设计过程。以电熨斗的配色设计为例，通过与普通交互式遗传算法对比，结果显示：1）用户对产品配色的知识背景差异会显著影响其认知度；2）配色设计过程的收敛性提升了37.5%，平均进化代数减小了2.4代。以上结果验证了本文方法符合用户主观认知特点，有助于提高产品交互配色设计的收敛性和进化效率。Abstract: Product color design plays an important role in shaping product style and corporate identity. In order to effectively assist industrial designers in product color design process and accurately reflect users' image perception of product color schemes, the interactive genetic algorithm was used and combined with users' cognition degree and fatigue degree in product color evaluation process, and a users' cognition noise model was proposed. By computing the similarity among evaluation value and color value of product color schemes respectively, the related parameters of cognition noise model were figured out and used for fitness adjustment of product color schemes which are given by users. The process of interactive product color design was put forward by integrating users' cognitive noise and interactive genetic algorithms. Taking the color design of electric iron as an example and comparing with the ordinary interactive genetic algorithms. Simulation results show that:1) knowledge background difference will significantly affect users' cognition of product color; 2) the convergence of color design process increased by 37.5%, and the average evolutionary algebra decreased by 2.4 generations. These results indicate that the proposed method could help to improve the convergence and evolution efficiency of interactive product color design.
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Key words:
- product color design /
- interactive genetic algorithms /
- cognitive noise /
- color image
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表 1 NIGA与IGA实验结果对比
算法类别 用户编号 进化代数 认知差异度阈值 疲劳度阈值 是否收敛 NIGA DM1 16 1 95 是 DM2 14 1 80 是 CM1 13 12 76 是 CM2 17 7 102 是 DF1 15 1 - 是 DF2 16 5 92 是 CF1 15 10 88 是 CF2 17 14 98 是 IGA DM3 17 - - 是 DM4 17 - - 是 CM3 20 - - 否 CM4 18 - - 是 DF3 16 - - 是 DF4 14 - - 是 CF3 20 - - 否 CF4 20 - - 否 
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[1] 陈鹏, 吕健, 潘伟杰.基于色彩方案重用的产品配色感性设计[J].工程设计学报, 2015, 22(6):546-551, 561 doi: 10.3785/j.issn.1006-754X.2015.06.006Chen P, Lv J, Pan W J. Product color design based on reuse of color scheme[J]. Chinese Journal of Engineering Design, 2015, 22(6):546-551, 561(in Chinese) doi: 10.3785/j.issn.1006-754X.2015.06.006 [2] Ding M, Dong W, Yang C C. Product color design based on multi-emotion[J]. Journal of Mechanical Science and Technology, 2013, 27(7):2079-2084 doi: 10.1007/s12206-013-0518-8 [3] 李孟山, 徐秋莹, 高德民, 等.融合混合智能方法和多用户意象的色彩决策系统[J].计算机辅助设计与图形学学报, 2017, 29(11):2091-2099 doi: 10.3969/j.issn.1003-9775.2017.11.015Li M S, Xu Q Y, Gao D M, et al. Color decision system based on hybrid intelligent method and Multi-users' Images[J]. Journal of Computer-Aided Design & Computer Graphics, 2017, 29(11):2091-2099(in Chinese) doi: 10.3969/j.issn.1003-9775.2017.11.015 [4] 刘炯宙, 李基拓, 陆国栋.色彩语义驱动的产品交互式遗传配色设计[J].计算机辅助设计与图形学学报, 2012, 24(5):669-676 doi: 10.3969/j.issn.1003-9775.2012.05.014Liu J Z, Li J T, Lu G D. Color scheme design through color semantic and interactive genetic algorithm[J]. Journal of Computer-Aided Design & Computer Graphics, 2012, 24(5):669-676(in Chinese) doi: 10.3969/j.issn.1003-9775.2012.05.014 [5] Tsai H C, Chou J R. Automatic design support and image evaluation of two-coloured products using colour association and colour harmony scales and genetic algorithm[J]. Computer-Aided Design, 2007, 39(9):818-828 doi: 10.1016/j.cad.2007.04.002 [6] 杨延璞, 陈登凯, 顾蓉, 等.基于色彩案例和灰度关联分析的产品配色设计方法[J].图学学报, 2016, 37(4):509-513 http://d.old.wanfangdata.com.cn/Periodical/gctxxb201604011Yang Y P, Chen D K, Gu R, et al. Product color design method based on color case and grey relational analysis[J]. Journal of Graphics, 2016, 37(4):509-513(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/gctxxb201604011 [7] 刘肖健, 李桂琴, 孙守迁.基于交互式遗传算法的产品配色设计[J].机械工程学报, 2009, 45(10):222-227 http://d.old.wanfangdata.com.cn/Periodical/jxgcxb200910034Liu X J, Li G Q, Sun S Q. Color mapping design from image to 3D product model[J]. Journal of Mechanical Engineering, 2009, 45(10):222-227(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/jxgcxb200910034 [8] Hsiao S W, Hsu C F, Tang K W. A consultation and simulation system for product color planning based on interactive genetic algorithms[J]. Color Research and Application, 2013, 38(5):375-390 doi: 10.1002/col.v38.5 [9] 杨延璞, 张涛, 顾蓉, 等.基于色彩心理效应的工程机械配色设计方法[J].筑路机械与施工机械化, 2016, 33(9):101-104 doi: 10.3969/j.issn.1000-033X.2016.09.026Yang Y P, Zhang T, Gu R, et al. Design of construction machinery colors based on psychological effects of color[J]. Road Machinery & Construction Mechanization, 2016, 33(9):101-104(in Chinese) doi: 10.3969/j.issn.1000-033X.2016.09.026 [10] 王家民, 张娜, 窦忠发, 等.面向用户感性需求的产品形态设计方法[J].机械科学与技术, 2015, 34(11):1653-1658 http://journals.nwpu.edu.cn/jxkxyjs/CN/abstract/abstract6201.shtmlWang J M, Zhang N, Dou Z F, et al. Product form design method oriented to users' perceptual demand[J]. Mechanical Science and Technology for Aerospace Engineering, 2015, 34(11):1653-1658(in Chinese) http://journals.nwpu.edu.cn/jxkxyjs/CN/abstract/abstract6201.shtml [11] 周勇, 巩敦卫.交互式遗传算法的噪声及降噪策略[J].控制理论与应用, 2008, 25(2):223-227 http://d.old.wanfangdata.com.cn/Periodical/kzllyyy200802008Zhou Y, Gong D W. Noises in interactive genetic algorithms and strategies for its reduction[J]. Control Theory & Applications, 2008, 25(2):223-227(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/kzllyyy200802008 [12] Saaty T L. The Analytic Hierarchy Process:Planning, Priority Setting, Resource Allocation (Decision Making Series)[M]. New York:McGraw-Hill, 1980 [13] Leung S O. A Comparison of psychometric properties and normality in 4-, 5-, 6-, and 11-point likert scales[J]. Journal of Social Service Research, 2011, 37(4):412-421 doi: 10.1080/01488376.2011.580697 -
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