Title page for etd-0711103-165401


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URN etd-0711103-165401
Author Chih-Hung Tzeng
Author's Email Address m9038621@student.nsysu.edu.tw
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Department Mechanical and Electro-Mechanical Engineering
Year 2002
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Using Local Invariant in Occluded Object Recognition by Hopfield Neural Network
Date of Defense 2003-06-23
Page Count 78
Keyword
  • Hopfield neural network
  • object recognition
  • Abstract In our research, we proposed a novel invariant in 2-D image contour recognition based on Hopfield-Tank neural network. At first, we searched the feature points, the position of feature points where are included high curvature and corner on the contour. We used polygonal approximation to describe the image contour. There have two patterns we set, one is model pattern another is test pattern. The Hopfield-Tank network was employed to perform feature matching. In our results show that we can overcome the test pattern which consists of translation, rotation, scaling transformation and no matter single or occlusion pattern.
    Advisory Committee
  • Chen-Wen Yen - chair
  • Chi-Cheng Cheng - co-chair
  • Innchyn Her - advisor
  • Files
  • etd-0711103-165401.pdf
  • indicate accessible in a year
    Date of Submission 2003-07-11

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