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Paper Currency Recognition And Defect Detection Under Low Resolution

Posted on:2007-06-16Degree:MasterType:Thesis
Country:ChinaCandidate:X Q FuFull Text:PDF
GTID:2178360185485808Subject:Computer Science and Technology
Abstract/Summary:PDF Full Text Request
Paper currency recognition is a popular issue in recent years, because it has a great future in the market. The paper currency sorter developed by designer plays an important role in bank area. Due to the reason of low resolution of paper currency image and high speed of paper currency sorter, so how to recognize paper currency under these conditions is a key problem. Then in pre-processing stage, for the allowance of the real time demand, we dispose the method of Hough transform and apply linear fitting to determine the border of paper currency to achieve localization and adjustment directly. By the analysis of based directional block feature extraction, we propose a new method of feature extraction based on geometry distance. In the design of classifier, we use the LVQ network to classify the feature and introduce a classifier with two layers. First classifier chooses two classes whose matching distance between it and paper currency is bigger than others from all class. Then in the second stage, we extract some new feature and improve the classifier to generate the last result. In the stage of defect detection for paper currency, we advances a homogeneity based algorithm for the detection of scratch and cracks appearing on paper currency, in which the homogeneity feature of the sensed paper currency image is first constructed to locate the pixels that probably been polluted, the image registration algorithm is subsequently used to overlay the sensed and reference paper currency image. At last, each probably polluted pixel on the sensed image is compared with its corresponding pixel on the reference image to estimate the contamination level...
Keywords/Search Tags:Image recognition, Feature extraction, Homogeneity
PDF Full Text Request
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