Wordlength estimation for the enhancement of hand-written word recognition

Although the problem of recognising machine printed words has been largely solved using available techniques, no ideal solution has been found for the problem of hand-written word recognition, especially with cursive script. This paper describes a method which can be used to estimate the length of hand-written words. The method shares a number of components with recognition techniques. It does not, however, aim to identify the word or any of its constituent characters; instead, it aims to directly identify the number of letters in the word as supporting information to aid more sophisticated recognition processes. The method of wordlength estimation has potential applications in many areas of text analysis. The work presented here concerns the application of the method in the field of automated bank cheque processing; more specifically, in the recognition of the legal amount field. It is also interesting to note that the method has been tested on two different languages, English and French (i.e. on words extracted from the legal amount field of both British and French cheques), in order to test its generic applicability.