On Detecting Edges.
Abstract
An edge in an image corresponds to a discontinuity in the intensity surface of the underlying scene. It can be approximated by a piecewise straight curve composed of edgels, i.e., short, linear edge elements, each characterized by a direction and a position. The approach to edgel-detection here, is to fit a series of one-dimensional surfaces to each window (kernel of the operator) and accept the surface description which is adequate in the least squares sense and has the fewest parameters. (A one-dimensional surface is one which is constant along some direction.) The tanh is an adequate basis for the step edge and its combinations are adequate for the roof edge and the line edge. The proposed method of step edgel detection is robust with respect to noise; for (step size / sigma sub noise) > or = 2.5, it has subpixel position localization (sigma sub position < 1/3) and an angular localization better than 10 deg; further, it is designed to be insensitive to smooth shading. These results are demonstrated by some simple analysis, statistical data and edgel-images. Also included is a comparison, of performance on a real image, with a typical operator (Difference of Gaussians). The results indicate that the proposed operator is superior with respect to detection, localization and resolution.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 1986
- Accession Number
- ADA174185
Entities
People
- Thomas O. Binford
- Vishvjit S. Nalwa
Organizations
- Stanford University