Image Chunking: Defining Spatial Building Blocks for Scene Analysis.

Abstract

Rapid judgements about the properties and spatial relations of objects are the crux of visually guided interaction with the world. Vision begins, however, with essentially pointwise representations of the scene, such as arrays of pixels or small edge fragments. For adequate time performance in recognition, manipulation, navigation, and reasoning, the processes that extract meaningful entities from the pointwise representations must exploit parallelism. This report develops a framework for the fast extraction of scene entities, based on a simple, local model of parallel computation. An image chunk is a subset of an image that can act as a unit in the course of spatial analysis. A parallel preprocessing stage constructs a variety of simple chunks uniformly over the visual array. On the basis of these chunks, subsequent serial processes locate relevant scene components and assemble detailed descriptions of them rapidly. This thesis defines image chunks that facilitate the most potentially time-consuming operations of spatial analysis - boundary tracing, area coloring, and the selection of locations at which to apply detailed analysis. Fast parallel processes for computing these chunks from images, and chunk-based formulations of indexing, tracing and coloring, are presented. These processes have been simulated and evaluated on the lisp machine and the connection machine.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1987
Accession Number
ADA187072

Entities

People

  • James V. Mahoney

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Applied Mathematics
  • Artificial Intelligence
  • Computational Science
  • Computer Science
  • Computer Vision
  • Connecting Rods
  • Detection
  • Electrical Engineering
  • Geometry
  • Image Processing
  • Information Processing
  • Parallel Computing
  • Pattern Recognition
  • Psychology
  • Recognition
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Mathematical Modeling and Probability Theory.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.