The design and implementation of a handheld scanner that can help sight-impaired or even blind users to manually scan and read text is discussed in this dissertation. A thorough investigation of all the elements involved in such a system is presented and optimal solutions are proposed. A unique velocity compensation technique based solely on optical information obtained by the scanning device is discussed and a real time segmentation technique based on topological properties (Quasi-Topological Codes) of connected segments is presented. A skew detection algorithm is discussed that can trace typed and printed text manual1y scanned with skew up to 15 degrees and can guide blind users to properly scan a document. Real time extraction of quasitopological codes for automatic text recognition and the hardware implementation is also discussed in this work. A hierarchical optical character recognition method is proposed which is based on syntactic and metric analysis of the Quasi-Topological Codes and their position in the scanned image. The proposed method can recognize characters stretched to approximately two times their original width or rotated by a few degrees. Finally, an automated iterative learning process is discussed which includes generalization of the recognition logic and dynamic adaptation of the syntactic and metric recognition rules. / Ph. D.