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Automatic recognition of handwritten characters using structural features

A system has been developed to automatically recognize handwritten letters by means of a data base composed of structural features rather than the more common technique of physical matching. Each letter is first separated and then concatenated into the handwritten word itself. The data base associated with each letter is encoded as a binary matrix representing basic invariant structural features. Recognizing procedures, both parallel and sequential, determine the relational height of each letter and the word itself and the height and width of each letter. Extracted features, such as continuity, loops, ovals and circles, openness and bowls are searched for and analyzed. Initially, the procedure is parallel, but then a sequential search of extra features, determined by the results obtained, is conducted to arrive at the final decision. The system permits context-free recognition of individual letters, thus allowing use of the system in a wide range of applications, such as in the detection of abbreviations. In addition, the resource and execution times of the system are modest so that it can be implemented on a wide range of computing equipment. Testing the system then for recognizing the six letters—a, b, e, h, i, and l—indicated an overall accuracy of 93% which was competitive with results obtained by human readers.