摘要
近年来,数字图像处理技术在纺织行业中得到了广泛的应用。为实现对织物经纬密度的高精度自动检测,以ARM架构处理器为核心硬件平台,配合Linux操作系统,设计了一套小型化、高精度的嵌入式织物经纬密度检测系统。该系统使用微型光学镜头采集织物图像,结合直方图均衡、频域滤波等多种图像检测算法,实现对织物经纬密度的高精度检测。硬件设计部分详细介绍了检测系统的系统框架与硬件结构;软件设计部分介绍了基于FIQ中断系统的高速CCD图像传感器驱动设计方案、综合多种图像处理算法的纱线密度检测算法等模块。实验表明,对于经典斜纹机织牛仔布,手动检测与自动检测的相对误差在1%以内,检测效果令人满意,设备可以批量生产。
In recent years, digital image processing technology has been widely used in the textile industry. In order to achieve high-precision automatic detection of the fabric warp and weft density, this paper designed a set of miniaturized embedded fabric weft density detector. The detector uses ARM architecture processor as the core hardware platform and running on the Linux operating system. The detector uses micro-optical lens to capture fabric images, and uses histogram equalization, frequency domain filtering and other image processing algorithms to detect the fabric warp and weft density. In this paper, the hardware design part introduces the system framework and hardware structure of the detection system in detail. The software design part introduces the driver design scheme of the high speed CCD image sensor based on the FIQ interruption system, and the weft density detection algorithm which synthesized various image processing algorithms. Experiments show that for the twill weave denim, the relative error between manual measurement and automatic measurement is less than 1%. The test results are satisfactory and the detector can be mass produced.
出处
《电子测量技术》
2017年第11期179-183,共5页
Electronic Measurement Technology
基金
上海市科委2015年创新行动计划项目(15111101804)
上海市科委2016年创新行动计划项目(16441905302)资助
关键词
经纬密度
ARM架构
数字图像处理
warp and weft density
ARM architecture
digital image processing
