1. A method of identifying sensitive expressions in images for a language with a large alphabet, the method to be performed using a computer and comprising: extracting an image from a computer-readable message; extracting image character-blocks from the image; predicting characters to which the character-blocks correspond using a multi-class learning model, wherein the multi-class learning model is trained using a derived list of sensitive characters which is a subset of the large alphabet; combining the predicted characters into string text; and searching the string text for matches with a predefined list of sensitive expressions in the language with the large alphabet.
9. The method of claim 1 , wherein the large alphabet is over two thousand distinct characters.