摘要
为研究客观、精确的服装穿着起拱性测试与评价方法,将20种机织物制作成裤筒进行穿着起拱实验。拍照保存织物的起拱形态,并运用激光扫描仪获取起拱部位的三维点云数据。对获取的数据进行预处理及特征提取,得到三维指标:起拱高度、起拱体积、经纬向最大起拱率;并提取起拱图像的二维灰度共生矩阵参数用于对比分析。经过对12块机织物的验证表明:起拱体积与主观评价等级的相关系数最高;本文提出的经纬向最大起拱率与起拱等级的相关性较好,其差值可用于判断起拱形状;利用激光扫描得到的三维指标预测起拱等级的准确率高于二维指标,且可克服机织物花纹图案、组织结构等对其的影响。
To study the objective evaluation of woven garment bagging behavior caused through daily wear,20 pieces of fabrics were made into pant-tubes for actual wearing and bagging.A camera and a 3-D laser scanner were used to acquire images and point cloud data of fabrics respectively.Then feature extraction was performed on the processed data to get the 3-D indexes:bagging height,bagging volume,warp and weft maximum bagging rate.At the same time,the 2-D gray level co-occurrence matrix indexes were extracted from the bagging image to compare with the 3-D indexes.12 pieces of fabrics were used for verification.The results showed that the highest coefficient of correlation with subjective grade is the bagging volume.The warp and weft maximum bagging rate has good correlation with the degree of bagging and the difference can be used to judge the bagging shape.The 3-D indexes obtained by 3-D laser scanning are more accurate than the 2-D indexes because it can overcome the influence of fabric pattern and fabric structure.
作者
郑晓萍
刘成霞
ZHENG Xiaoping;LIU Chengxia(School of Fashion Design & Engineering, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China;Zhejiang Province Engineering Laboratory of Clothing Digital Technology, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, China)
出处
《纺织学报》
EI
CAS
CSCD
北大核心
2021年第5期143-149,共7页
Journal of Textile Research
基金
浙江省自然科学基金项目(LY20E050017)
浙江省大学生科技创新活动计划暨新苗人才计划项目(2019R406072)
浙江理工大学研究生优秀学位论文基金项目(2019M28)。
关键词
服装起拱
三维激光扫描
最大起拱率
特征提取
客观评价
garment bagging
3-D laser scanning
maximum bagging rate
feature extraction
objective evaluation
