Research On Identifying Methods Of RMB Banknote Denomination Based On Machine Vision

Identifying of banknote denomination is a necessary function module on all financial equipments. In recent years, with rapid development of China's national economy, the demand of automatic banknote detaching-machine and other financial equipments becomes extremely urgent. On the basis of references about recognition of banknote denomination at abroad and home, contraposing to RMB self-characteristics, this thesis designs denomination recognition method based on image processing and neural network technology.On the basis of RMB banknote images obtained in advance, this method is composed of image noise filtering, declining image adjusting, image locating and segmentation, feature extraction, denomination recognition and several other components.â‘ Declining image adjusting is a more crucial tache. In the course of adjusting declining image, this thesis puts forward a method of calculating the slope of the upper frame line with line fit, consequently, the declining angle is obtained, and then we can rotate the image based on the above angle.â‘¡In the process of image locating and segmentation, a gray projection method is adopted. According to the obvious differences between image background and objectives, we can accurately locate the border of target image to separate target image from background image, and then normalize the target image.â‘¢In the process of feature extraction, the characteristics are extracted with similar axis-symmetry masks according to the specialty of the RMB image.â‘£In the process of denomination recognition, we adequately use the abilities of parallel processing and high fault tolerance for NN, apply BP algorithm to denomination identifying of banknote. This recognition method not only recognizes new and slightly polluted banknotes, but also for defected and old but still circulating banknote is strongly robust, too. Through experiments for a certain number of RMB images acquired by the scanner, on the condition of a small amount of rejection, this method can achieve 100 percent correct recognition rate. It can fully meet the current domestic automatic recognition requirements for RMB denomination and will have good prospects for the practical application.