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A Trainable Low-level Feature Detector

Hall, PM, Owen, MJ and Collomosse, JP (2004) A Trainable Low-level Feature Detector

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Abstract

We introduce a trainable system that simultaneously filters and classifies low-level features into types specified by the user. The system operates over full colour images, and outputs a vector at each pixel indicating the probability that the pixel belongs to each feature type. We explain how common features such as edge, corner, and ridge can all be detected within a single framework, and how we combine these detectors using simple probability theory. We show its efficacy, using stereo-matching as an example.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Authors :
AuthorsEmailORCID
Hall, PMUNSPECIFIEDUNSPECIFIED
Owen, MJUNSPECIFIEDUNSPECIFIED
Collomosse, JPUNSPECIFIEDUNSPECIFIED
Date : August 2004
Identification Number : https://doi.org/10.1109/ICPR.2004.1334279
Contributors :
ContributionNameEmailORCID
PublisherIEEE, UNSPECIFIEDUNSPECIFIED
Depositing User : Symplectic Elements
Date Deposited : 28 Mar 2017 13:10
Last Modified : 28 Mar 2017 13:10
URI: http://epubs.surrey.ac.uk/id/eprint/805272

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