At present, the most technology of counting money is to use the money counter in financial fields. The paper presents a
new method for automatic counting paper money which is based on image processing technology. Firstly, the paper
money image is acquired by CCD. After analyzing the feature of image, we find that in Cr-space the edge of each paper
money is enhanced. Then we use the north-west sobel operator for filtering and north sobel operator for detecting edge.
Although the image-processed better highlight the edge of each paper money, the edge is rough and its variance is high.
It is hardly to threshold the image for getting the single-pixel edge linked. After Different segmentation algorithm was
been used for deriving the edge of paper money, we find the Two-dimensional Histogram θ-division algorithm is suitable
for our purpose. The experimental result is proved satisfied. The detecting rate reached 100% in controlled environment
for RMB. However, if we want to detect other kinds of paper money such as dollar, there also have several problems to
be solved.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.