A Fast Straight-Line Growing Algorithm for Sheet-Counting with Stacked-Paper Images
The measurement of stacked-sheet quantity is an essential step in packaging and printing production,and its counting accuracy has a direct impact on economic efficiency of related companies.With its noncontact,nondestructivity and real-time measurement merits,the machine vision method has been widely applied to quality control for high-end printing products.In this paper,we aim to circumvent the fringe detection problem in stacked-sheet images by introducing a level line guided line-segment growing algorithm.Then,a high-accuracy measurement of stack quantity can be realized with the improvement of precision and completeness on fringe identification.Our work mainly consists of three parts: 1) A unidirectional gradient operator is adopted to eliminate multiple responses on a single fringe.2) The gradient magnitude and level-line direction are combined to improve the growth of line support regions in noisy environment.3) To completely identify each sheet fringe,a connected component analysis algorithm is integrated to remedy the local gap in line detection.The performance of our algorithm has been verified in experiments using various kinds of printed-papers with a large number.It is shown that the long-term measurement error is less than 0.75‰ and is sufficient to meet the requirement of factory applications.
Machine vision Stacked sheet counting Line segment detection LSD
ZhenXiao Gang Yang Shuo Changyan Xiao
College of Electrical and Information Engineering,Hunan University Changsha,P.R. China
国际会议
Chinese Conference on Pattern Recognition, CCPR(2014年全国模式识别学术会议)
长沙
英文
418-425
2014-11-01（万方平台首次上网日期，不代表论文的发表时间）