Detecting registration failure | IEEE Conference Publication | IEEE Xplore

Detecting registration failure


Abstract:

This paper presents a new approach to evaluation of registration using a general discriminative learning model that is independent of the type of registration method. We ...Show More

Abstract:

This paper presents a new approach to evaluation of registration using a general discriminative learning model that is independent of the type of registration method. We select features by association of a registration with a set of metrics (pixel based, patch based and histogram based statistics) and learn a classifier that discriminates mis-registrations from correct registrations using Adaboost. Experiments on a set of wireless capsule endoscopy (CE) images and images extracted from minimally invasive surgical endoscopic video data are presented. Results show that the proposed method outperforms any single classifier.
Date of Conference: 28 June 2009 - 01 July 2009
Date Added to IEEE Xplore: 07 August 2009
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Conference Location: Boston, MA, USA

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