Writer-independent Offline Recognition of Handwritten Ethiopic Characters

This paper presents writer-independent offline handwritten character recognition for Ethiopic script. The recognition is based on the characteristics of primitive strokes that make up characters. The spatial relationships of primitives whose combinations form complex structures of Ethiopic characters are used as a basis for recognition. Although this approach efficiently recognizes properly written characters, the recognition rate drops for characters where the spatial relationships of their primitives could not be drawn. This happens mostly when the connections between primitives are not properly written, which is a common case in handwriting. To complement the recognition, we classify characters based on the characteristics of their primitives, resulting in grouping of characters in a five-dimensional space. Once the type of characters is identified, recognition can be achieved with a minimal set of information from their spatial relationships. A comprehensive database is also developed to standardize the evaluation of research works on offline Ethiopic handwriting recognition systems. Our proposed system is tested is with the database and experimental results are reported.