Title :
Edge detection using the linear model
Author :
Kay, Steven N. ; Lemay, Gerald I.
Author_Institution :
University of Rhode Island, Kingston, RI, USA
Abstract :
An edge detector based on the linear model is developed which utilizes the generalized likelihood ratio for statistical hypothesis testing. The performance of this detector is analytically and experimentally compared to that of a gradient operator (Sobel) and is shown to have a slightly higher detection rate for a given false alarm rate. The detector is also invariant to multiplicative changes of the gray-scale values of the image.
Keywords :
Convolution; Detectors; Image converters; Image edge detection; Maximum likelihood estimation; Performance analysis; Random variables; Robots; Testing; Vectors;
Conference_Titel :
Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '84.
DOI :
10.1109/ICASSP.1984.1172663
