7. A method for detecting text, comprising: employing a processor to execute computer executable code stored on a storage medium to perform the following acts: identifying one or more connected components associated with unlabeled data under text detection; utilizing the connected components to extract a feature vector for each connected component; utilizing a boosted classifier to classify each connected component represented by its respective feature vector; employing inferred labels to bin the connected components across a plurality of bins; computing properties for each bin; and utilizing a transductive classifier to classify the connected components as a function of the feature vectors and corresponding computed bin properties.
7. A method for detecting text, comprising: employing a processor to execute computer executable code stored on a storage medium to perform the following acts: identifying one or more connected components associated with unlabeled data under text detection; utilizing the connected components to extract a feature vector for each connected component; utilizing a boosted classifier to classify each connected component represented by its respective feature vector; employing inferred labels to bin the connected components across a plurality of bins; computing properties for each bin; and utilizing a transductive classifier to classify the connected components as a function of the feature vectors and corresponding computed bin properties. 8. The method of claim 7 , further comprising training the boosted classifier by: receiving labeled training data that includes connected components, text labels and nontext labels; extracting a feature vector for each connected component in the training data; and training the boosted classifier with the labels and feature vectors.