Image analysis – Pattern recognition – Classification
Reexamination Certificate
2005-03-31
2009-08-04
Mehta, Bhavesh M (Department: 2624)
Image analysis
Pattern recognition
Classification
C382S176000, C707S793000
Reexamination Certificate
active
07570816
ABSTRACT:
The subject invention relates to facilitating text detection. The invention employs a boosted classifier and a transductive classifier to provide accurate and efficient text detection systems and/or methods. The boosted classifier is trained through features generated from a set of training connected components and labels. The boosted classifier utilizes the features to classify the training connected components, wherein inferred labels are conveyed to a transductive classifier, which generates additional properties. The initial set of features and the properties are utilized to train the transductive classifier. Upon training, the system and/or methods can be utilized to detect text in data under text detection, wherein unlabeled data is received, and connected components are extracted therefrom and utilized to generate corresponding feature vectors, which are employed to classify the connected components using the initial boosted classifier. Inferred labels are utilized to generate properties, which are utilized along with the initial feature vectors to classify each connected component using the transductive classifier.
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Bargeron David M
Simard Patrice Y
Viola Paul A
Akhavannik Hadi
Lee & Hayes PLLC
Mehta Bhavesh M
Microsoft Corporation
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