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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

采用灰度图像分析的方法，测量了不同组织密度的平针织物的视觉特征，规则折叠和不规则折叠棉织物的皱折外观，以及包括褶皱状褶皱和不规则褶皱在内的随机皱纹织物的视觉松弛行为。以数字图像的灰度均值、从灰度共生矩阵中提取的角二阶矩、相关性、对比度、熵和分维作为视觉特征参数。这些图像信息参数可用于表征平针织物的美感、皱纹织物的视觉特征和皱纹恢复的视觉松弛行为。图像中的颜色使用NTSC_RGB颜色系统表示。将RGB图像转换为L*…更多C*H*图像。计算了L*、C*和H*像的共现对比度(CON)。发现CON是描述圆点图案对比度效果和彩色阴影的一个很好的参数。运用并置混色逻辑，从多彩图案的整体色彩印象出发，运用彩色图像分析方法评价多彩布料图案的冷暖程度。得出结论：多色布料图案的暖色、中性和冷色图像可以通过色调角度进行评价。基于RGB颜色空间的颜色特征分析被应用于多种织物的颜色纹理表征。通过因子分析检验了它们的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*。得到图像中所有像素的L*、a*和b*的平均值分别为AVE-L*、AVE-a*和AVE-b*。分光计测量的L*、a*和b*与纯色图像分析的AVE-L*、AVE-a*和AVE-b*有很好的一致性。较少