Text image compression based on statistical analysis and classification of the vertical line elements - Иванов, Владимир Георгиевич; Ломоносов, Юрий Вячеславович; Любарский, Михаил Григорьевич (Eastern-European Journal of Enterprise Technologies, 2014)
A new original method for text data image compression is presented. Vertical line elements rather than connecting symbols of the text image are used as the main processing element. The given probability model quite accurately describes possible distortions of the vertical line elements, caused by printing and scanning noise. Based on the accepted probability model and statistical analysis methods, minimum most plausible set of undistorted elements in the entire set of the investigated vertical line elements is found. For each vertical element, the probability that this element is a distortion of an element of the set of undistorted line elements is found. Classification of the vertical line elements of the text image is based on a probabilistic assessment of the classified elements belonging to a single center. The end result of the proposed method is forming a dictionary of connecting symbols of the text image, where each class is represented by its most probable image and an allocation map of connecting symbols on the plane of the studied image. The proposed text image processing method has allowed to obtain a relatively high compression ratio with good quality of the reconstructed image. Comparison with the currently best special text image compression algorithm - JB2, within the format DjVu, has shown that the proposed algorithm has the advantage in data compression ratio of about 37% in processing a text page image with a resolution of 300 dpi.