12. The method of claim 11 , wherein the feature vector comprises a string of bits where each bit corresponds to presence or absence of a feature in the character-block.
11. A method of training a multi-class learning model so that the model predicts characters to which image character-blocks correspond, the method to be performed using a computer and comprising: providing a set of sample messages with sensitive expressions in a language with a large alphabet, wherein the sensitive expressions are embedded in images; extracting said images from the sample messages; extracting image character-blocks from said images; receiving correlations between the image-character blocks and corresponding characters in said language; converting the image character-blocks to feature vectors with the corresponding characters as class labels for the feature vectors; and using the feature vectors and the class labels to train said learning model.