This paper presents a novel approach for feature extraction in spatial domain to recognize segmented (isolated) Kannada numerals using artificial neural networks. Artificial neural systems represent the promising new generation of information processing networks to develop intelligent machines which can be used as classifier. The ability of neural networks to learn by ordinary experience, as we do, and to take sensitive decisions give them the power to solve problems found intractable or difficult for traditional computation. In this paper, the development of handwritten Kannada numeral recognition system using spatial features and neural networks is reported. Handwritten numerals are scan converted to binary images and normalized to a size of 30 x 30 pixels. The features are extracted using spatial co ordinates and are classified successfully using the feed forward neural network classifier.

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Handwritten Kannada Numerals Artificial Neural Network Feature Extraction Pattern Classification