Title

Edge Detection Using the Linear Model

Document Type

Article

Date of Original Version

1-1-1986

Abstract

An edge detector based on the linear model is developed which utilizes the generalized likelihood ratio for statistical hypothesis testing. The detector is invariant to multiplicative changes in the grayscale values of the image. Hence, thresholding based histogram segmentation is not required. The performance of this detector is analytically and experimentally compared to that of a gradient operator (Sobel) and is shown to have only a slightly poorer detection rate for a given false alarm rate. Copyright © 1986 by the Institute of Electrical and Electronics Engineers, Inc.

Publication Title

IEEE Transactions on Acoustics, Speech, and Signal Processing

Volume

34

Issue

5

Share

COinS