Palmprint Recognition via Sparse Coding Spatial Pyramid Matching Representation of SIFT Feature

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• 关键词：Sparse coding ; Spatial pyramid matching ; Palmprint recognition
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9967
• 期：1
• 页码：235-243
• 全文大小：646 KB
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• 作者单位：Ligang Liu (21)
  Jianxin Zhang (21)
  Aoqi Yang (21)
  
  21. Key Lab of Advanced Design and Intelligent Computing, Ministry of Education, Dalian University, Dalian, People’s Republic of China
  
• 丛书名：Biometric Recognition
• ISBN：978-3-319-46654-5
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9967

文摘

Spatial pyramid matching using sparse coding (ScSPM) algorithm can construct the palmprint image descriptors which may effectively express local features and global features of palmprint image. In the paper, we adopt sparse coding and max pooling instead of vector quantization coding and sum pooling to extract descriptors, and it improves the nonlinear coding to linear coding. Then, the linear SVM classifier is applied to replace the nonlinear classifier in pyramid matching. We apply this algorithm to the recognition of palmprint images and exactly analyze the effects of parameters on the recognition, including the size of a complete dictionary and sparse coding parameter. The experimental results illuminate the excellent effectiveness of the ScSPM algorithm for palmprint recognition.