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Study of Palmprint Feature Extraction Algorithm Based on Multi-resolution Analysis and Gray Level Co-Occurence Matrix

Author: HeXiaoJian
Tutor: WangFuMing
School: University of North
Course: Signal and Information Processing
Keywords: Palmprint recognition Wavelet decomposition GLCM Feature Extraction
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 93
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Abstract


In recent years, with the rapid development of information science and technology , information security is facing unprecedented challenges . The biometric uses the body's own physiological characteristics and behavioral characteristics for authentication , providing a reliable guarantee for the information security problems . At present , the development of biometric identification technology is mature and has been in many areas has been widely used . Since palmprint area , more details , injury and incomplete palmprint sufficient identification information and other features , palmprint identification system to become major research topic in recent years, many universities and research institutions . In addition, based on of palmprint biometric technology research and application is far less extensive fingerprint identification . Therefore, from the scientific point of view or from the point of view of market demand , can palmprint recognition has important theoretical value and social value . The core content of this study is to feature extraction . Around this core to carry out the following work : (1 ) The first two chapters introduce biometric identification technology and palmprint identification system , focus on the the palmprint identification process of the pretreatment and feature extraction of two modules in detail elaboration. (2) the palmprint image binarization, location, to normalized and enhancement pretreatment eliminate palmprint offset and rotation , the palmprint image contrast , to prepare for subsequent palmprint characteristics extraction . (3 ) after pretreatment palmprint images using wavelet decomposition subgraph at all levels , and then calculate the individual gray level co-occurrence matrix characteristic parameters palmprint image features can be more fully reflect the characteristic parameters , based on multi resolution analysis and the GLCM palmprint feature extraction . ( 4) artificial matching method , and accounting recognition accuracy of the proposed algorithm , and the recognition rate simply based on GLCM feature extraction algorithm are compared , to verify the effectiveness and superiority of the proposed algorithm .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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