Abstract: A method of identifying the script of a line of text by first assigning a weight to each n-gram in a group of documents of known scripts, where each n-gram is a sequence of numbers representing k-mean cluster centroids of a known script to which character segments in the documents of known scripts most closely match. A line of text is identified, where the line of text is made up of pixels. The identified line of text is cropped so that only a percentage of the pixels remain. The cropped line is vertically and horizontally rescaled into gray-scale pixels. The vertical gray-scale pixels are replaced with the sequence number of a k-means cluster centroid of a known script to which it most closely matches. The n-grams of the number sequence that represents the line of text is scored against the n-gram weights of the documents of known text. The highest score of the line of text is identified and compared to the scores of the documents of known scripts.