A Renormalization Group Approach to Image Processing. A New Computational Method for 3-Dimensional Shapes in Robot Vision, and the Computational Complexity of the Cooling Algorithms

Abstract

During the period of the contract, 6/15/86-7/31/89, we have develop: I). A parallel multilevel-multiresolution algorithm for Image Processing and low-level Robot vision tasks, II). A Bayesian/Geometric Framework for 3-D shape estimation from 2-D images, appropriate for object recognition and other Robot tasks III). A procedure for rotation and scale invariant representation (coding) and recognition of textures; a computationally efficient algorithm for estimating Markov Random Fields, IV). We have obtained mathematical results concerning convergence and speed of convergence of computational algorithms such as the annealing algorithm, and have studied mathematically the consistency and asymptotic normality of Maximum Likelihood Estimators for Gibbs distributions. Keywords: Computer vision. (KR)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 30, 1989
Accession Number
ADA214247

Entities

People

  • Basilis Gidas

Organizations

  • Brown University

Tags

Communities of Interest

  • Autonomy
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Applied Mathematics
  • Asymptotic Normality
  • Bayesian Networks
  • Computational Science
  • Computer Science
  • Computer Vision
  • Estimators
  • Image Processing
  • Information Processing
  • Information Science
  • Mathematics
  • Object Recognition
  • Recognition
  • Statistics
  • Three Dimensional
  • Two Dimensional

Readers

  • Computer Vision.
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Autonomy