Colors of textile materials are the first parameter of quality evaluated by consumers and a key component considered in selecting printed fabric. In the textiles industry, digital printed fabric analysis is one of the...Colors of textile materials are the first parameter of quality evaluated by consumers and a key component considered in selecting printed fabric. In the textiles industry, digital printed fabric analysis is one of the basic elements in successfully utilizing a color mechanism scheme and objectively evaluating fabric color alterations. Precise color measurement, however, is mostly used in sample analysis and quality inspection which help to produce reproducible or similar product. It is important that for quality inspection, the color of the product should be measured as a necessary requirement of quality control whether the product is to be accepted or not. Presented in this study is an unsupervised segmentation of printed fabrics patterns using mean shift algorithm and color measurements over the segmented regions of printed fabric patterns. The results established a consistent and reliable color measurement of multiple color patterns and appearance with the established range without any interactions.展开更多
RGB色彩空间中各色彩分量间存在强相关性,图像发生失真会改变各分量间的相关性.基于此,本文提出了一种新的通用无参考图像质量评价方法.首先,根据人类视觉对RGB色彩空间中绿色分量更为敏感的颜色感知特性,提取了G分量MSCN系数及其4方向...RGB色彩空间中各色彩分量间存在强相关性,图像发生失真会改变各分量间的相关性.基于此,本文提出了一种新的通用无参考图像质量评价方法.首先,根据人类视觉对RGB色彩空间中绿色分量更为敏感的颜色感知特性,提取了G分量MSCN系数及其4方向邻域系数的统计特征;其次,在分析RGB色彩空间中R、G及B分量间相关性的基础上,分别计算RGB色彩空间各色彩分量及其纹理、相位间的互信息,利用互信息作为统计特征来描述其各分量间的相关性;进而,结合上述统计特征,分别利用SVR和SVC构建无参考图像质量评价模型和图像失真类型识别模型;最后,在LIVE、CSIQ及TID2008图像质量评价数据库上进行了算法与DMOS(Different mean opinion score)的相关性、失真类型识别及计算复杂性等方面的实验.实验结果表明,本文方法的评价结果与人类主观评价具有高度的一致性,在LIVE数据库上的斯皮尔曼等级相关系数和皮尔逊线性相关系数均在0.942以上;而且,图像失真类型识别模型的识别准确率也高达93.59%,明显高于当今主流无参考图像质量评价方法.展开更多
文摘Colors of textile materials are the first parameter of quality evaluated by consumers and a key component considered in selecting printed fabric. In the textiles industry, digital printed fabric analysis is one of the basic elements in successfully utilizing a color mechanism scheme and objectively evaluating fabric color alterations. Precise color measurement, however, is mostly used in sample analysis and quality inspection which help to produce reproducible or similar product. It is important that for quality inspection, the color of the product should be measured as a necessary requirement of quality control whether the product is to be accepted or not. Presented in this study is an unsupervised segmentation of printed fabrics patterns using mean shift algorithm and color measurements over the segmented regions of printed fabric patterns. The results established a consistent and reliable color measurement of multiple color patterns and appearance with the established range without any interactions.
文摘RGB色彩空间中各色彩分量间存在强相关性,图像发生失真会改变各分量间的相关性.基于此,本文提出了一种新的通用无参考图像质量评价方法.首先,根据人类视觉对RGB色彩空间中绿色分量更为敏感的颜色感知特性,提取了G分量MSCN系数及其4方向邻域系数的统计特征;其次,在分析RGB色彩空间中R、G及B分量间相关性的基础上,分别计算RGB色彩空间各色彩分量及其纹理、相位间的互信息,利用互信息作为统计特征来描述其各分量间的相关性;进而,结合上述统计特征,分别利用SVR和SVC构建无参考图像质量评价模型和图像失真类型识别模型;最后,在LIVE、CSIQ及TID2008图像质量评价数据库上进行了算法与DMOS(Different mean opinion score)的相关性、失真类型识别及计算复杂性等方面的实验.实验结果表明,本文方法的评价结果与人类主观评价具有高度的一致性,在LIVE数据库上的斯皮尔曼等级相关系数和皮尔逊线性相关系数均在0.942以上;而且,图像失真类型识别模型的识别准确率也高达93.59%,明显高于当今主流无参考图像质量评价方法.