Searching for a letter or a word in historical documents is a practical challenge due to the various degradations present in such documents and the wide variance of handwriting. Searching in historical Hebrew documents is somewhat harder because of high similarities among Hebrew characters. In order to determine the features and their combinations appropriate for recognizing Hebrew script, we study a range of known features using a Dynamic Time Warping algorithm. In addition we describe a novel meth od for feature-based searching, which uses a number of models for the same character. This method is based on our original DTW algorithm that can match fragments of several models of the same character to match a query character. Consequently, we are not limited to any particular model of the character set. Application of this method leads to a significant improvement, even when using a small set of models.