Deformable Topological Templates for Image Analysis.

Abstract

The main achievements of this proposal has been the introduction of a new family of global but sparse image features consisting of geometric arrangements of local responses. These features can serve as building blocks for template models, allowing for explicit modeling of the variability of the object family, and efficient computation of the template match. These features can also be accessed through decision trees to provide very accurate and efficient shape classifiers.

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Document Details

Document Type
Technical Report
Publication Date
Aug 10, 1996
Accession Number
ADA316810

Entities

People

  • Yali Amit

Organizations

  • University of Chicago

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Classification
  • Computations
  • Computer Vision
  • Data Compression
  • Diagnostic Imaging
  • Image Compression
  • Images
  • Information Theory
  • Machine Learning
  • Object Recognition
  • Recognition
  • Scientists
  • Students
  • Template Patterns
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Computational Fluid Dynamics (CFD)
  • Neural Network Machine Learning.
  • Systems Analysis and Design