On Edge Detection,

Abstract

Edge detection is the process that attempts to characterize the intensity changes in the image in terms of the physical processes that have originated them. A critical, intermediate goal of edge detection is the detection and characterization of significant intensity changes. This paper discusses this part of the edge detection problem. To characterize the types of intensity changes derivatives of different types, and possibly different scales, are needed. Thus, we consider this part of edge detection as a problem in numerical differentiation. We show that numerical differentiation of images is an ill-posed problem in the sense of Hadamard. Differentiation needs to be regularized by a regularizing filtering operation before differentiation. This shows that this part of edge detection consists of two steps, a filtering step and a differentiation step. We discuss recent results on the behavior and the information content of zero crossings obtained with filters of different sizes. These results imply a specific order in the sequence of filtering and differentiation operations. Topological properties are preserved by level-crossings.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1984
Accession Number
ADA148573

Entities

People

  • T. Poggio
  • V. Torre

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Change Detection
  • Computer Vision
  • Detection
  • Detectors
  • Differential Equations
  • Equations
  • Filters
  • Filtration
  • Geometric Forms
  • Geometry
  • Image Processing
  • Information Processing
  • Mathematical Filters
  • Pattern Recognition
  • Three Dimensional
  • Two Dimensional

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Image Processing and Computer Vision.
  • Mathematical Modeling and Probability Theory.