基于遗传算法的织物图案构建自动化

Omema Ahmed, M. S. Abid, Aiman Junaid, S. S. Raza
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引用次数: 0

摘要

本文介绍了利用遗传算法从随机生成的种子进化织物图案。图案是从随机的,通常是暗淡的图像颜色演变成明亮的多色图案,在本质上是审美上的。本文打算解决的主要问题是在模式设计过程中引入完全自动化,这在历史上一直依赖于人工仲裁者来判断中间输出的质量。取而代之的是,该算法使用图像本身存在的固有潜在特征来评估图像的质量。我们的算法考虑了图像的颜色分布、全局对比度和总体暗度评分来评估生成的图案的质量。为了创造感觉更自然的不同模式,我们尝试了不同的方法。其中包括使用l系统和图像处理技术,试图构建一个看起来更像人类的模式,而不仅仅是基本的数字艺术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automation of Fabric Pattern Construction using Genetic Algorithms
This paper introduces the use of Genetic Algorithms to evolve fabric patterns from randomly generated seeds. The patterns are evolved from random, often dull coloring of the image, to bright multi-color patterns that are aesthetically pleasing in nature. The main problem that this paper intends to solve is to introduce complete automation in the design process of patterns, which have historically been dependent upon human arbitrators to judge the quality of intermediate outputs. In its stead, the proposed algorithm evaluates the quality of the image using inherent latent features present in the image itself. Our algorithm takes into account the distribution of color, global contrast, and the overall dullness score of the image to evaluate the quality of the generated patterns. To create diverse patterns that feel more natural, different approaches are experimented with. These include the use of L-systems and image processing techniques, in a bid to construct a pattern which seems more human-like, rather than just rudimentary digital art.
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