Image based object classification
AssigneeSicpa Holding SA
InventorsGuillaume HEUSCH, Nicolas PICAN
Life of this patent
Estimating the term…
Abstract
A method for classifying an object in image data to one out of a set of classes using a classifier, said image data comprising an image of the object, each class indicating a property common to a group of objects, the method comprising the steps of obtaining said classifier used to estimate for an input feature vector a probability for each of the set of classes, one probability indicating whether the input feature vector belongs to one class; extracting a feature vector from said image data; using the obtained classifier to estimate the probabilities for the extracted feature vector; and evaluating the estimated probabilities for determining whether the object does not belong to any one of the set of classes based using a quality indicator.
Claims18
A method for classifying an object in image data to one out of a set of classes using a classifier, said image data comprising an image of the object, each class indicating a property common to a group of objects, the method comprising the steps of:
- obtaining said classifier used to estimate for an input feature vector a probability for each of the set of classes, one probability indicating whether the input feature vector belongs to one class;
- extracting a feature vector from said image data;
- using the obtained classifier to estimate the probabilities for the extracted feature vector;
- and
- evaluating the estimated probabilities for determining whether the object does not belong to any one of the set of classes based using a quality indicator.
A device for classifying an object in image data, to one of a set of classes using a classifier, said image data comprising an image of the object, each class indicating a property common to a group of objects, the device comprising processing resources being configured to:
- obtain said image data;
- obtain said classifier used to estimate for an input feature vector a probability for each of the set of classes, one probability indicating whether the input feature vector belongs to one class;
- extract a feature vector from said image data;
- use the obtained classifier to estimate the probabilities for the extracted feature vector;
- and to
- evaluate the estimated probabilities for determining whether the object does not belong to any one of the set of classes based using a quality indicator.
Dependencies are inferred from the claim text.