摘要
针对纸病会影响纸张的外观和使用性能的现象,对基于机器视觉的纸病检测方法进行了研究。分析了黑斑、亮斑、褶皱的图像特征。通过图像去噪、灰度分析、阈值分割、图像二值化实现了黑斑亮斑的检测;再通过边缘检测、图像二值化、形态学处理及Hough变换完成对褶皱的检测。
Aiming at the phenomenon that paper disease can affect the appearance and usage performance of paper,this paper investigated the disease detection method based on machine vision,analyzed the image features of the wrinkle,black and bright spots.The detection of black and bright spots was realized through the image de-noising,analysis of gray level,threshold segmentation,two binary images.And the detection of the wrinkle was realized through the edge detection,two binary images,morphological processing and Hough transformation.This work may provide a convenience for the automation of paper disease detection.
出处
《机械工程与自动化》
2016年第2期37-39,共3页
Mechanical Engineering & Automation
基金
北京林业大学科技创新计划项目(YX2013-24)
关键词
机器视觉
纸病检测
阈值分割
HOUGH变换
machine vision
paper disease detection
threshold segmentation
Hough transformation
