||Today, biometrics has been applied to personal recognition popularly, & more important. For instance, the PIN (Personal Identification Number), which was used to ATM (Automated teller machine), caused the loss of bank almost 30 thousands of millions due to false acceptance . In 1991, Sep 11, terrorists attacked New York & caused inestimable loss of lives & cost; for avoid this matter, United States do their best to have the most correct identification in every where & the unique of biometric is just what we want.|
Iris recognition, one kind of biometrics, has been adopted so many years, but the methods of recognition almost are very complex & consume much resource. Since the characteristics of IRIS are made up by different patterns, in this thesis, we try to apply some methods of image processing to the data base, which is provided by CASIA , & hope to do well recognition. We only catch 4 blocks of IRIS in the image, which are pure & distinct, make up them to be a new block called as characteristic block. After emphasized the image of characteristic block, the matching rate of pictures could be 81.25%, & 96.3% in person matching if we count the mean & variance of characteristic blocks. Compare to the thesis which use the same CASIA database , follow authors suggestion, we eliminate some images that are not suitable for recognition. After that, the useable rate of images is 87.04%, & we got the 3.03% of EER.
Finally, we try to implement this system & catch images via CCD directly replace pre-caught images , the matching rate is 100% when we test total 10 persons.
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