One of the standard problems of edge- and line-detecting algorithms is to determine the most appropriate size of the convolution-operator for the particular task, maximising the conflicting goals of resolution and sensitivity. Here we suggest a novel approach to scale selection, where the scale size varies dynamically with the convolution output: the stronger the output, the smaller the spatial scale. This principle has been applied to two types of feature-detection algorithms, and shown to perform well for both one- and two-dimensional images.
An Adaptive Approach To Scale Selection For Line and Edge-detection / M. C. MORRONE;A. NAVANGIONE;D. BURR. - In: PATTERN RECOGNITION LETTERS. - ISSN 0167-8655. - STAMPA. - 16:(1995), pp. 667-677. [10.1016/0167-8655(95)00017-B]
An Adaptive Approach To Scale Selection For Line and Edge-detection
BURR, DAVID CHARLES
1995
Abstract
One of the standard problems of edge- and line-detecting algorithms is to determine the most appropriate size of the convolution-operator for the particular task, maximising the conflicting goals of resolution and sensitivity. Here we suggest a novel approach to scale selection, where the scale size varies dynamically with the convolution output: the stronger the output, the smaller the spatial scale. This principle has been applied to two types of feature-detection algorithms, and shown to perform well for both one- and two-dimensional images.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.