一种基于边缘特征的纸币污损检测方法

污损检测是纸币清分中的一个重要环节 .针对纸币上常见的笔迹及撕裂污损,提出了一种基于图像边缘特征的检测方法 .首先将待检测图像与参考图像进行图像配准,然后采用Kirsch算子提取两图像的边缘信息,并提出了一种符合人的主观感受的边缘强度差的计算方法,在此基础上提取的污损特征,对于图像中新增加的边缘信息十分敏感,而对各像素的灰度值、边缘强度值的相对变化则具有很强的抗干扰性 .将纸币划分为若干个相互重叠的子区域,通过对子区域内污损特征统计,来判定该子区域内是否存在污损 .实验证明,该方法识别率高且稳定、可靠,满足实际要求 .该方法已应用到实际的纸币清分系统中 .

An Edge-Based Defect Detection Algorithm for Paper Currency

Defect detection is an essential step in paper currency sorting. In this paper, an edge-based algorithm is proposed to detect the scratches and cracks appearing frequently on paper currency. An area-based image registration algorithm is used to overlay the sensed and referenced paper currency images. To ensure accurate correlation with the subjective feelings of human beings, an edge intensity differential of two images is then constructed from the edge information extracted by the Kirsch operator. The defect feature extracted from edge intensity differential is sensitive to the odd edge-information, and is robust to the gray (or edge ) intensity change. The paper currency image is divided into several overlapping subzones. Within each subzone, the defect feature is calculated to estimate the level of contamination. The proposed algorithm has already been applied to a practical sorting system, and the experimental results reveal that it is robust when applied to low quality paper currency.