  This paper describes a geometry based technique for feature extraction
applicable to segmentation-based word recognition systems. The proposed system
extracts the geometric features of the character contour. This features are
based on the basic line types that forms the character skeleton. The system
gives a feature vector as its output. The feature vectors so generated from a
training set, were then used to train a pattern recognition engine based on
Neural Networks so that the system can be benchmarked.
