Dissertation > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices

The Design of Iris Recognition Classifier Based on Neural Network

Author CaoGuoHui
Tutor ChenSanBao
School Wuhan University of Technology
Course Control Theory and Control Engineering
Keywords Iris Classifier Neural Networks MATLAB
CLC TP391.4
Type Master's thesis
Year 2006
Downloads 168
Quotes 4
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Authentication of modern highly information-oriented society , people have penetrated into every aspect of daily life . The same time , due to the rapid development of transportation, communication and network technology , the range of human activities is increasing , the authentication difficulty and importance has become increasingly acute . For such a populous country , authentication has broad application prospects and is of strategic importance . Financial , security , network , e-commerce , and both need reliable authentication . The traditional use of passwords and other authentication method is easily forgotten , counterfeiting and other shortcomings , no longer meet the needs of modern digital society . Advantages of biometric - based biometric authentication technology using human to distinguish the identity of the person , these biometric with a stable , convenient, and difficult to forge , and in recent years has become a hotspot authentication . Commonly used in biometrics include fingerprints , palm prints , iris , face , voice , signature and handwriting . Iris as authentication characteristics , uniqueness , stability , and can acquire resistance , non- invasive advantages . Compared with other methods , the iris having a higher accuracy. According to statistics , the iris recognition error rate is the the various biometric lowest . Therefore , the use of iris authentication technology gradually get the attention of academia and the business community . In this paper, the iris recognition based on neural network classifier design , a detailed description of the iris recognition background , purpose , meaning , the status quo and prospects . Compare the positioning algorithm and feature extraction algorithm , from which a reasonable algorithm to image processing in the the iris digital image processing . In classifier design classifier past are based Hamming Dayton distance classifier design , we propose to design a classifier for iris recognition using neural networks . And successfully scaling rotation, translation and scale invariance iris recognition . Besides, the paper by Image Processing Toolbox and Neural Network Toolbox in MATLAB , introduced in MATLAB Image Processing Toolbox and Neural Network Toolbox in varying degrees .

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