Pattern‐driven design method is an important data‐driven design method for printed fabric motif design in textiles and clothing industry. We introduce a novel framework for automatic design of color patterns in real‐world fabric motif images. The novelty of our work is to formulate the recognition of an underlying color pattern element as a spatial, multi‐target tracking, classification, segmentation and similarity association process using a new and efficient color feature encoding method. The proposed design method is based on pattern‐driven color pattern recognition and indexing from the element image database. A series of color pattern recognition algorithms are used for color and pattern feature extraction. The local statistical corner features and Markov random field model are used for motif unit tiling detection and conversion. The color feature encoding problem is modeled in a gray‐scale color difference optimization problem, which can be solved quickly by existing algorithms. Color pattern feature matching, segmentation and indexing techniques are then used to locate and replace the elements in the motif unit image with similar elements in the database. Experiments show that the approach proposed in this study is effective for color pattern recognition and printed fabric motif design.

中文翻译：

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图案驱动的彩色图案识别，用于印花织物图案设计

图案驱动设计方法是纺织品和服装行业中印花织物图案设计的重要数据驱动设计方法。我们介绍了一种新颖的框架，用于在现实世界中的织物图案图像中自动设计颜色图案。我们工作的新颖性在于，使用一种新型高效的颜色特征编码方法，将对基础颜色模式元素的识别公式化为空间，多目标跟踪，分类，分割和相似度关联过程。所提出的设计方法基于元素图像数据库中模式驱动的颜色模式识别和索引。一系列颜色模式识别算法用于颜色和模式特征提取。局部统计角特征和马尔可夫随机场模型用于主题单元拼贴检测和转换。颜色特征编码问题以灰度色差优化问题为模型，可通过现有算法快速解决。然后使用颜色图案特征匹配，分割和索引技术来定位和替换主题单元图像中的元素，并将其替换为数据库中的相似元素。实验表明，本研究提出的方法对于彩色图案识别和印花织物图案设计是有效的。