Identification of Fraktur and Latin Scripts in German Historical Documents Using Image Texture Analysis

This article proposes an algorithm for script identification by textural analysis of the image corresponding to the script types. In the first phase, each letter is modeled by the equivalent script type, which is determined by its position in the baseline area. Then, feature extraction is carried out. It is based on the script type cooccurrence pattern analysis. The obtained features of the script are stored for further analysis. The difference in script characteristics contributes to the diversity of the extracted features, which simplify the feature classification obtained by an extension of a state-of-the-art classification tool called Genetic Algorithms Image Clustering for Document Analysis. Accordingly, it represents the key element in the decision-making process of script identification. The proposed method is tested on an example of German printed documents, which contain Latin and Fraktur scripts. The experiment shows correct results, which is promising.