Alemayehll, Nega (PhD)Alemu, Worku (PhD)Tadesse, Nigussie2020-06-152023-11-182020-06-152023-11-182000-05http://etd.aau.edu.et/handle/12345678/21583The advent and wide application of Information Technology (IT) has brought changes on the way we perform things. One area where IT particularly computers has showed significant improvement in efficiency and effectiveness of activities is by handling routine, repetitive, boring and error prone tasks. Among such tasks bank check reading is the one that can be handled by computers in a stable manner using the OCR technology. In this piece of work an attempt was made to adopt a recognition algorithm for handwritten Amharic text. To achieve this target some preprocessing. segmentation and normalization techniques implemented for other scripts were reviewed. The Feature oj hand printed Amharic text in general and hand printed legal amounts in particular were studied. Based on the identified Features some of the preprocessing. segmentation and normalization algorithms were implemented and tested on a set of hand printed data collected using sample checks. In addition, different feed forward neural networks with back-propagation learning algorithm were implemented and the test results as well as the procedure of the test are recorded. Finally recommendations are forwarded pointing out some points for further consideration.enInformation ScienceThesis