A framework for low level feature extraction
ECCV '94 Proceedings of the third European conference on Computer Vision (Vol. II)
Amharic Character Recognition using a Fast Signature Based Algorithm
IV '03 Proceedings of the Seventh International Conference on Information Visualization
Vision with Direction: A Systematic Introduction to Image Processing and Computer Vision
Vision with Direction: A Systematic Introduction to Image Processing and Computer Vision
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OCR technology of Latin scripts is well advanced in comparison to other scripts. However, the available results from Latin are not always sufficient to directly adopt them for other scripts such as the Ethiopic script. In this paper, we propose a novel approach that uses structural and syntactic techniques for recognition of Ethiopic characters. We reveal that primitive structures and their spatial relationships form a unique set of patterns for each character. The relationships of primitives are represented by a special tree structure, which is also used to generate a pattern. A knowledge base of the alphabet that stores possibly occurring patterns for each character is built. Recognition is then achieved by matching the generated pattern against each pattern in the knowledge base. Structural features are extracted using direction field tensor. Experimental results are reported, and the recognition system is insensitive to variations on font types, sizes and styles.