Detecting registration failure
| Autor: | Rajesh Kumar, Gerard E. Mullin, Sharmishtaa Seshamani, Gregory D. Hager, Srdan Bejakovic, Purnima Rajan, Themistocles Dassopoulos |
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| Rok vydání: | 2009 |
| Předmět: |
Boosting (machine learning)
Contextual image classification business.industry Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Image registration Pattern recognition law.invention ComputingMethodologies_PATTERNRECOGNITION Capsule endoscopy law Histogram Computer vision Artificial intelligence AdaBoost business Classifier (UML) Discriminative learning |
| Zdroj: | ISBI |
| DOI: | 10.1109/isbi.2009.5193150 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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