服饰刺绣图案的自动提取与色块分割

为避免人工视觉方法完成刺绣图案花纹提取过程中存在的耗时费力、主观性强等缺陷,结合传统服饰织物,采用图像分析方法实现刺绣图案的自动提取,并进行色值分析。首先采用数码相机实现刺绣织物类图案的采集;接着利用平滑滤波滤除图像中的噪声信号,并将图像从RGB颜色空间转换到Lab颜色空间;然后利用K-Means聚类分析方法对a,b分量进行聚类分析;最后根据聚类分析结果获得准确的图案及色彩信息。研究结果表明:图像处理方法可以实现刺绣图案的自动分割,这种自动化图案分割对一般刺绣图案的自动提取均能使用,这为服饰图案的审美研究提供了全新的样本整理途径。

Automatic extraction on embroidered patterns of traditional costumes

Manual extraction of embroidered patterns with human vision is time consuming, lab-intensive and subjective. To overcome these difficulties, image analysis was adopted to complete the automatic recognition and aesthetic analysis of the embroidered patterns on the traditional consumes fabrics. Digital camera was used to realize the image acquisition of embroidered fabrics. Image smoothing was then applied to the fabric image to remove the noise information and the fabric image was converted to Lab color space from RGB color space. K-Means clustering method was adopted to realize the color clustering based on a and b components in Lab color space. The accurate pattern and color information of the embroidered fabric were obtained based on the clustering results. The research results show that the image analysis can achieve the automatic extraction of embroidered patterns and the new segmentation method can be applied to quite a number of embroidered fabric patterns, which provides a brand new way for sample collection of aesthetic research.