Title :
Optimising edge detection
Author :
Witts, W. I C ; Otto, G.P.
Author_Institution :
Dept. of Comput. Sci., Univ. Coll. of London, UK
Abstract :
A feature detector is described that bases its research on a set of probability distributions that describe the situations in which the feature can be found. The result is a measure of the probability of the feature occurring at a particular point. The probabilities required to operate this detector can be automatically derived from test images, although it can be altered to detect any kind of feature. The output from this detector is a set of probabilities that represent the likelihood of and edge occurring at each point in the image. These need only to be summed to find the probability of an edge over an interval, and, in a similar fashion, images can be subsampled in order to find probable edges to subpixel accuracy
Keywords :
optimisation; pattern recognition; probability; edge detection; feature detector; optimisation; pattern recognition; probability distributions; subpixel accuracy; Computer science; Computer vision; Detectors; Educational institutions; Image edge detection; Image segmentation; Signal processing; Training data;
Conference_Titel :
Pattern Recognition, 1988., 9th International Conference on
Conference_Location :
Rome
Print_ISBN :
0-8186-0878-1
DOI :
10.1109/ICPR.1988.28222