权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

SENSORY EVALUATION AND VISUAL IMFORMATION OF COLOR TEXTURE AND FABRIC APPEARANCE USING IMAGE ANALYSIS

使用图像分析对颜色纹理和织物外观进行感官评估和视觉信息

基本信息

批准号：
16500488
负责人：
MORI Toshio
金额：
$ 1.78万
依托单位：
Gifu Women's University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2004
资助国家：
日本
起止时间：
2004 至 2007
项目状态：
已结题

项目摘要

Gray scale image analysis is applied for the measurement of visual features of plain knitted fabrics with different kinds of stitch densities, crease appearance of regularly or irregularly folded cotton cloth, and visual relaxation behavior of randomly wrinkled cloths including wrinkles like ripple and irregularly folded creases. Mean of the gray level for the digital image, the angular second moment, correlation, contrast and entropy which were extracted from the gray level co-occurrence matrix, and the fractal dimension are measured as visual feature parameters. These image information parameters is found to be useful for characterizing the beauty of plain knitted fabrics, the visual features of creased cloths and the visual relaxation behavior of wrinkle recovery.Color Image analysis is applied to the characterization of color contrast and colored shadow phenomenon of polka-dotted patterns. Colors in an image are expressed in the NTSC_RGB color system. RGB images are converted to L* … More C*H* images. The co-occurrence contrast (CON) is calculated for L*, C* and H* images. CON is found to be a good parameter to describe the contrast effect and colored shadow of polka-dotted patterns. Color image analysis is used to evaluate the warmth and coolness of multicolored patterns of cloth from a whole color impression of multicolored patterns by applying the logic of juxtaposition color mixture. It is concluded that warm, neutral and cool color images of multicolored patterns of cloth can be evaluated by hue angles. Color feature analysis by using RGB color space is applied to the characterization of color textures of many fabrics. The relationship between their sensory evaluation values and the visual feature parameters is examined by the factor analysis. In color image analysis of color fading for color patterned fabrics, L*, a* and b* are computed for each pixel in the image using the CIELAB formula. Mean values of L*, a* and b* for all pixels in the image are obtained as AVE-L*, AVE-a* and AVE-b*, respectively. There is a good agreement between L*, a* and b* by spectrometer measurements and AVE-L*, AVE-a* and AVE-b* by image analysis for solid color. Less

灰度图像分析用于测量不同针迹密度的平纹针织物的视觉特征、规则或不规则折叠棉布的折痕外观、以及包括波纹状皱纹和不规则折叠折痕在内的随机皱纹布料的视觉松弛行为。数字图像的灰度平均值、从灰度共生矩阵中提取的角二阶矩、相关性、对比度和熵以及分形维数被测量为视觉特征参数。这些图像信息参数对于表征平纹针织物的美感、折痕布料的视觉特征以及皱纹恢复的视觉松弛行为非常有用。彩色图像分析应用于圆点图案的色彩对比度和彩色阴影现象的表征。图像中的颜色以 NTSC_RGB 颜色系统表示。 RGB 图像转换为 L* … 更多 C*H* 图像。计算 L*、C* 和 H* 图像的共生对比度 (CON)。 CON被发现是描述圆点图案的对比效果和彩色阴影的一个很好的参数。色彩图像分析是运用并置混色的逻辑，从五彩图案的整体色彩印象来评价布料五彩图案的冷暖性。结论：可以通过色相角来评价布料多彩图案的暖色、中性色和冷色图像。使用RGB颜色空间的颜色特征分析被应用于许多织物的颜色纹理的表征。通过因子分析考察其感官评价值与视觉特征参数之间的关系。在彩色图案织物褪色的彩色图像分析中，使用 CIELAB 公式计算图像中每个像素的 L*、a* 和 b*。图像中所有像素的 L*、a* 和 b* 的平均值分别获得为 AVE-L*、AVE-a* 和 AVE-b*。光谱仪测量的 L*、a* 和 b* 与纯色图像分析的 AVE-L*、AVE-a* 和 AVE-b* 之间有很好的一致性。较少的